{"access":{"advertiser_pricing_url":"https://aidevboard.com/pricing","catalog_url":"https://aidevboard.com/api/v1/catalog","description":"Public read endpoints are open and free. API keys are optional for stable agent identity and keyed hourly throttling.","docs_url":"https://aidevboard.com/docs","mode":"open","register_url":"https://aidevboard.com/api/v1/register"},"degraded":false,"estimated":false,"has_next":true,"jobs":[{"id":"cec41a2d-61db-466d-97a8-9cfca9b8f6dd","company_id":"a0000000-0000-0000-0000-000000000003","title":"Staff Software Engineer, Full Stack - Gen AI ","slug":"staff-software-engineer-full-stack-gen-ai-014fb300","description":"Our Generative AI Data Engine powers the world’s most advanced LLMs and generative models through world-class RLHF (Reinforcement Learning with Human Feedback), human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI.\n This is a horizontal, high-impact L6 Staff Fullstack Engineer \u0026 Architect position reporting directly to the Director of Contributor Engineering.\n Instead of being tied to a single domain, your scope is spread across all Contributor (CB) teams (including Allocation, Growth,  Trust \u0026 Safety, Pay, and Allocations). Together, these teams power Scale’s AI data operations - from building high-impact datasets that push the boundaries of LLM capabilities, to optimizing contributor onboarding and incentives, to safeguarding data integrity through advanced trust, safety, and security measures. They work at the intersection of ML, operations, and analytics to ensure we deliver the highest-quality data at scale.\n You will act as an organizational architect and tech lead, dynamically embedding yourself into the highest-priority projects across the org to guarantee execution, unblock teams, and successfully ship mission-critical initiatives. Concurrently, you will lead the long-term technical evolution of our stack, transforming the core architecture to ensure it is highly sustainable, scalable, and fundamentally AI-native.\n You will:\n \n Deploy flexibly into critical, fast-moving product initiatives across the CB organization\n Lead the architectural overhaul of our platform infrastructure, making it highly sustainable, robust, and optimized for deep integration with LLMs and foundation models.\n Lead architecture decisions for scalability, reliability, and performance\n Mentor and uplevel engineers across the team\n Partner with product and leadership to shape roadmap and priorities\n Own large, ambiguous problem spaces end-to-end\n Work across backend, frontend, and ML systems\n \n Ideally you'd have: \n \n 7+ years of full-time engineering experience, post-graduation, with a proven track record of operating as a Tech Lead, Architect, or Principal Engineer.\n Track record of shipping high-quality products and features at scale\n Experience tinkering with or productizing LLMs, vector databases, and the other latest AI technologies\n Proficient in Javascript/Typescript, and SQL\n Experience with Kubernetes\n Experience with major cloud providers (AWS, Azure, GCP)\n Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend. \n Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is:\n $252,000 — $315,000 USD \n PLEASE NOTE:  Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. \n About Us: \n At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst \u0026 Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. \n We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status.  \n We are committed to wor","salary_min":252000,"salary_max":315000,"location":"New York, NY","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["reinforcement-learning","llm","embeddings","generative-ai","fullstack"],"apply_url":"https://job-boards.greenhouse.io/scaleai/jobs/4713608005","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-09T18:54:54Z","expires_at":"2026-08-14T14:01:50.579966Z","created_at":"2026-07-10T14:01:27.296205Z","updated_at":"2026-07-15T14:01:50.706933Z","company_name":"Scale AI","company_slug":"scale-ai","company_logo_url":"https://www.google.com/s2/favicons?domain=scale.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/cec41a2d-61db-466d-97a8-9cfca9b8f6dd"},{"id":"78bb5e81-4dfe-4ed2-af4d-f819687a5629","company_id":"e455f75a-a424-4955-9844-afebe8ea6eb4","title":"Cloud Infrastructure Architect, Okta Federal","slug":"cloud-infrastructure-architect-okta-federal-be26a5b7","description":"Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk.\n \n  Technology, Data, and Insights (TDI) is on a mission to accelerate Okta's scale and growth. We bring world-class business acumen and technology expertise to every interaction. We also drive cross-functional collaboration and are focused on delivering measurable business outcomes.\n The TDI Infrastructure Engineering team owns the foundational platforms that power Okta's business — from cloud infrastructure and AI platform delivery to network engineering, developer productivity, observability, and client platforms. We are a team of builders who design and operate at scale, and we are in the middle of a strategic transformation: evolving our cloud practice from a self-service model into a managed, opinionated platform that the entire business can rely on.\n The Cloud Platform Architect Opportunity\n Okta Federal, Inc. is looking for a dedicated Cloud Platform Architect for TDI Infrastructure Engineering — the technical authority for how we design, build, and evolve the cloud infrastructure that underpins our AI platform and the broader workloads running across the business. You will define the architectural standards, patterns, and strategies that the Cloud Platform Engineering team builds to, and you will serve as a key partner to AI, security, and productivity architects as we scale Okta's cloud capabilities to meet increasing business demand.\n This is a hands-on builder role. We are not looking for someone who advises from a distance — we need someone who has shipped cloud infrastructure at scale and brings the credibility and depth to make sound architectural decisions in a fast-moving environment. You will operate at a critical moment: Okta's AI platform is scaling rapidly, our cloud platform team is transforming, and the foundational decisions made now will define the trajectory of our infrastructure for years.\n This role reports directly to the Director of Infrastructure Engineering.\n What You'll Be Doing\n \n Define and own Okta's Cloud Platform architecture — establish reference architectures, design standards, and guardrails that bring consistency, security, and reliability to workloads running across the business\n Lead the architecture for Kubernetes and EKS — design and evolve our cluster strategy, multi-tenancy model, networking topology, and security posture as the platform scales to support AI agent workloads and diverse business unit deployments\n Elevate Okta's AI platform — partner with AI architects and platform engineers to evolve our agent and model-serving infrastructure from its current state to a production-grade, scalable platform capable of supporting broad business adoption\n Drive multi-cloud strategy — build the evaluation framework and decision criteria for when and how Okta leverages AWS, Azure, and Google Cloud; ensure workload placement is intentional and optimized for performance, cost, and capability\n Serve as the technical anchor for the Cloud Platform Engineering team — raise the architectural quality of everything the team designs and builds as we complete the transformation from account vending to a managed platform model\n Partner cross-functionally with AI, security, and productivity architects, product managers, and business unit stakeholders to ensure cloud infrastructure decisions align with Okta's product, compliance, and operational requirements — including support for federal programs and FedRAMP environments\n Partner cross-functionally to design cloud-native solutions that can be effectively adapted for air-gapped, self-hosted environments like US Secret (SIPRNet) and US Top Secret (JWICS).\n Help architect and validate foundational Kubernetes and infrastructure designs within unclassified AWS GovCloud sandboxes. You will ensure these commercial-side designs translate seamlessly when tested against emulators that simulate the strict constraints of air-gapped networks.\n Ensure our commercial cloud platform architecture shares foundational DNA with our highly regulated deployments, aligning with DoD-centric frameworks like the USAF's \"Big Bang\" architecture and utilizing Iron Bank hardened containers where applicable.\n \n What You'll Bring to the Role\n \n 10+ years of hands-on cloud infrastructure experience with deep, demonstrated expertise in one or more major cloud providers (AWS, GCP, or Azure) — including compute, networking, storage, IAM, and managed services at enterprise scale; AWS experience is preferred given our current environmen","salary_min":244000,"salary_max":336000,"location":"Washington, DC","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["fine-tuning","mlops","cloud","agents","data-pipeline","embeddings","infrastructure"],"apply_url":"https://www.okta.com/company/careers/opportunity/8004104?gh_jid=8004104","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-09T17:52:28Z","expires_at":"2026-08-14T14:11:18.197322Z","created_at":"2026-07-10T14:08:46.130561Z","updated_at":"2026-07-15T14:11:18.324586Z","company_name":"Okta","company_slug":"okta","company_logo_url":"https://www.google.com/s2/favicons?domain=okta.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/78bb5e81-4dfe-4ed2-af4d-f819687a5629"},{"id":"9b918972-172d-4cf7-bea5-24effecf6a52","company_id":"41d4f321-d748-4a4e-962f-dd5d23de3e43","title":"Principal Engineer Tech Lead, Embodied AI \u0026 Off-Board Performance Evaluation","slug":"principal-engineer-tech-lead-embodied-ai-off-board-performance-evaluation-69ed84ad","description":"Mission Summary: \n Motional is a leading autonomous driving company on a mission to make driverless vehicles a safe, reliable, and accessible reality. Backed by Hyundai Motor Group, Motional is at the forefront of the physical AI revolution. Motional isn’t just building first-of-its-kind technology; we are transforming transportation to create safer streets and more sustainable mobility options.\n The Systems Readiness and Performance team is the crucial bridge between software development and real-world deployment. We are responsible for driving system design, for verifying and validating the autonomy stack, and for defining, measuring, and validating system performance targets. We work closely with stakeholders in autonomy, infrastructure, and operations to build the definitive safety case for the commercial launch of our fully driverless IONIQ 5 robotaxis in Las Vegas later this year.\n We are seeking a talented Principal Engineer to technically oversee the design, development, and deployment of a novel Embodied AI and Large Language Model (LLM)-based monitoring framework for off-board scenario understanding, intelligence evaluation, and root cause analysis. While this role will pioneer future off-board Vision-Language-Action (VLA) integrations for off-board analysis, it requires strong foundations as an Autonomous Vehicle Performance Metrics developer.\n You will lead the creation of a specialized, off-board evaluation layer that consumes AV drive logs and fleet data to automatically infer scenario safety and assess driving intelligence without running live on the vehicle. Your architectural designs will integrate with internal systems to form a complete pipeline that identifies safety incidents, enriches them with structured context, and conducts detailed root cause analysis to provide the Autonomy team with actionable direction. If you are an innovative individual contributor with a passion for overseeing the integration of complex, scalable data pipelines and state-of-the-art Embodied AI frameworks, we encourage you to apply. \n What You'll Be Doing: \n \n Embodied AI \u0026 LLM Framework Oversight: Technically oversee the architecture to identify, describe, and enrich events in historical vehicle logs using Multimodal LLMs.\n Multi-Modal Data Fusion: Oversee the off-board ingestion and fusion of semantic scene descriptions, ego-centric kinematics, and internal autonomy telemetry to create a holistic diagnostic context for LLM inference.\n Prompt Engineering \u0026 Model Integration: Develop structured prompting templates utilizing Contextual Prompting (CP), Chain-of-Thought (CoT), and In-Context Learning (ICL) to evaluate scenarios.\n AI Inference \u0026 Evaluation Scalability: Architect the integration of foundation models into the Metrics Engine (ME), designing efficient cascade filtering and log slice parallelization strategies to scale high-volume LLM inference across simulation and on-road drive logs while managing computational latency and costs.\n AV Performance Metrics Foundations: Define, design, and implement key metrics to evaluate autonomous vehicle performance, such as lane change capability, oscillations, and braking.\n Driving Policy Integration: Deploy and manage a Retrieval-Augmented Generation (RAG) vector database containing codified AV Driving Policies to ground off-board LLM evaluations in specific Operational Design Domains.\n Cross-Functional Technical Leadership: Serve as a technical escalation point and collaborate with Autonomy (Planner, Prediction, Perception) and Systems teams to deliver high-signal, enriched events.\n Advanced Physical AI R\u0026D: Drive the transition toward Direct Vector-LLM Fusion utilizing emerging Physical AI ecosystems and open-weights Vision-Language-Action (VLA) models to process telemetry off-board without text-translation bottlenecks. \n \n What We're Looking For: \n \n 10+ years of professional experience in software engineering, applied AI/ML, or autonomous vehicle systems development.\n Bachelor's degree in Computer Science, Engineering, Robotics, or a related field.\n Proven experience working with Large Language Models (LLMs) and Vision-Language Models (VLMs) for reasoning, parsing, and scene description.\n Experience with parameter-efficient fine-tuning and deploying open-weights models on internal infrastructure.\n Familiarity with local and cloud vector databases, such as LanceDB, for housing output vector embeddings.\n Experience with adversarial scenario generation and closed-loop simulation environments.\n Strong background leveraging software to develop frameworks, libraries, and tools for calculating and aggregating AV performance metrics.\n Strong analytical and problem-solving skills, particularly in the context of complex system performance evaluation.\n Expert-level proficiency in Python and strong understanding of software development principles. \n \n Bonus Points (not required): \n \n Experience working with autonomous vehicle sensor data, including its processing and in","salary_min":200000,"salary_max":275000,"location":"Boston, MA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"principal","tags":["embeddings","cloud","generative-ai","fine-tuning","robotics","data-pipeline","llm","rag"],"apply_url":"https://motional.com/open-positions/?gh_jid=7799671003#/7799671003","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-09T14:10:05Z","expires_at":"2026-08-14T14:07:59.682275Z","created_at":"2026-07-10T14:05:50.176304Z","updated_at":"2026-07-15T14:07:59.82836Z","company_name":"Motional","company_slug":"motional","company_logo_url":"https://www.google.com/s2/favicons?domain=motional.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/9b918972-172d-4cf7-bea5-24effecf6a52"},{"id":"9cb51051-fb08-47c1-a84d-e0937ebe010e","company_id":"41d4f321-d748-4a4e-962f-dd5d23de3e43","title":"Principal Engineer Tech Lead, Embodied AI \u0026 Off-Board Performance Evaluation","slug":"principal-engineer-tech-lead-embodied-ai-off-board-performance-evaluation-50d09b91","description":"Mission Summary: \n Motional is a leading autonomous driving company on a mission to make driverless vehicles a safe, reliable, and accessible reality. Backed by Hyundai Motor Group, Motional is at the forefront of the physical AI revolution. Motional isn’t just building first-of-its-kind technology; we are transforming transportation to create safer streets and more sustainable mobility options.\n The Systems Readiness and Performance team is the crucial bridge between software development and real-world deployment. We are responsible for driving system design, for verifying and validating the autonomy stack, and for defining, measuring, and validating system performance targets. We work closely with stakeholders in autonomy, infrastructure, and operations to build the definitive safety case for the commercial launch of our fully driverless IONIQ 5 robotaxis in Las Vegas later this year.\n We are seeking a talented Principal Engineer to technically oversee the design, development, and deployment of a novel Embodied AI and Large Language Model (LLM)-based monitoring framework for off-board scenario understanding, intelligence evaluation, and root cause analysis. While this role will pioneer future off-board Vision-Language-Action (VLA) integrations for off-board analysis, it requires strong foundations as an Autonomous Vehicle Performance Metrics developer.\n You will lead the creation of a specialized, off-board evaluation layer that consumes AV drive logs and fleet data to automatically infer scenario safety and assess driving intelligence without running live on the vehicle. Your architectural designs will integrate with internal systems to form a complete pipeline that identifies safety incidents, enriches them with structured context, and conducts detailed root cause analysis to provide the Autonomy team with actionable direction. If you are an innovative individual contributor with a passion for overseeing the integration of complex, scalable data pipelines and state-of-the-art Embodied AI frameworks, we encourage you to apply. \n What You'll Be Doing: \n \n Embodied AI \u0026 LLM Framework Oversight: Technically oversee the architecture to identify, describe, and enrich events in historical vehicle logs using Multimodal LLMs.\n Multi-Modal Data Fusion: Oversee the off-board ingestion and fusion of semantic scene descriptions, ego-centric kinematics, and internal autonomy telemetry to create a holistic diagnostic context for LLM inference.\n Prompt Engineering \u0026 Model Integration: Develop structured prompting templates utilizing Contextual Prompting (CP), Chain-of-Thought (CoT), and In-Context Learning (ICL) to evaluate scenarios.\n AI Inference \u0026 Evaluation Scalability: Architect the integration of foundation models into the Metrics Engine (ME), designing efficient cascade filtering and log slice parallelization strategies to scale high-volume LLM inference across simulation and on-road drive logs while managing computational latency and costs.\n AV Performance Metrics Foundations: Define, design, and implement key metrics to evaluate autonomous vehicle performance, such as lane change capability, oscillations, and braking.\n Driving Policy Integration: Deploy and manage a Retrieval-Augmented Generation (RAG) vector database containing codified AV Driving Policies to ground off-board LLM evaluations in specific Operational Design Domains.\n Cross-Functional Technical Leadership: Serve as a technical escalation point and collaborate with Autonomy (Planner, Prediction, Perception) and Systems teams to deliver high-signal, enriched events.\n Advanced Physical AI R\u0026D: Drive the transition toward Direct Vector-LLM Fusion utilizing emerging Physical AI ecosystems and open-weights Vision-Language-Action (VLA) models to process telemetry off-board without text-translation bottlenecks. \n \n What We're Looking For: \n \n 10+ years of professional experience in software engineering, applied AI/ML, or autonomous vehicle systems development.\n Bachelor's degree in Computer Science, Engineering, Robotics, or a related field.\n Proven experience working with Large Language Models (LLMs) and Vision-Language Models (VLMs) for reasoning, parsing, and scene description.\n Experience with parameter-efficient fine-tuning and deploying open-weights models on internal infrastructure.\n Familiarity with local and cloud vector databases, such as LanceDB, for housing output vector embeddings.\n Experience with adversarial scenario generation and closed-loop simulation environments.\n Strong background leveraging software to develop frameworks, libraries, and tools for calculating and aggregating AV performance metrics.\n Strong analytical and problem-solving skills, particularly in the context of complex system performance evaluation.\n Expert-level proficiency in Python and strong understanding of software development principles. \n \n Bonus Points (not required): \n \n Experience working with autonomous vehicle sensor data, including its processing and in","salary_min":200000,"salary_max":275000,"location":"Las Vegas, Nevada, United States","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"principal","tags":["embeddings","robotics","data-pipeline","generative-ai","cloud","rag","fine-tuning","autonomous-vehicles"],"apply_url":"https://motional.com/open-positions/?gh_jid=7799673003#/7799673003","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-09T14:10:04Z","expires_at":"2026-08-14T14:07:59.867702Z","created_at":"2026-07-10T14:05:50.099596Z","updated_at":"2026-07-15T14:07:59.996378Z","company_name":"Motional","company_slug":"motional","company_logo_url":"https://www.google.com/s2/favicons?domain=motional.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/9cb51051-fb08-47c1-a84d-e0937ebe010e"},{"id":"bd8a325e-af13-4567-9c46-1409196e7f88","company_id":"41d4f321-d748-4a4e-962f-dd5d23de3e43","title":"Principal Engineer Tech Lead, Embodied AI \u0026 Off-Board Performance Evaluation","slug":"principal-engineer-tech-lead-embodied-ai-off-board-performance-evaluation-8c5b455c","description":"Mission Summary: \n Motional is a leading autonomous driving company on a mission to make driverless vehicles a safe, reliable, and accessible reality. Backed by Hyundai Motor Group, Motional is at the forefront of the physical AI revolution. Motional isn’t just building first-of-its-kind technology; we are transforming transportation to create safer streets and more sustainable mobility options.\n The Systems Readiness and Performance team is the crucial bridge between software development and real-world deployment. We are responsible for driving system design, for verifying and validating the autonomy stack, and for defining, measuring, and validating system performance targets. We work closely with stakeholders in autonomy, infrastructure, and operations to build the definitive safety case for the commercial launch of our fully driverless IONIQ 5 robotaxis in Las Vegas later this year.\n We are seeking a talented Principal Engineer to technically oversee the design, development, and deployment of a novel Embodied AI and Large Language Model (LLM)-based monitoring framework for off-board scenario understanding, intelligence evaluation, and root cause analysis. While this role will pioneer future off-board Vision-Language-Action (VLA) integrations for off-board analysis, it requires strong foundations as an Autonomous Vehicle Performance Metrics developer.\n You will lead the creation of a specialized, off-board evaluation layer that consumes AV drive logs and fleet data to automatically infer scenario safety and assess driving intelligence without running live on the vehicle. Your architectural designs will integrate with internal systems to form a complete pipeline that identifies safety incidents, enriches them with structured context, and conducts detailed root cause analysis to provide the Autonomy team with actionable direction. If you are an innovative individual contributor with a passion for overseeing the integration of complex, scalable data pipelines and state-of-the-art Embodied AI frameworks, we encourage you to apply. \n What You'll Be Doing: \n \n Embodied AI \u0026 LLM Framework Oversight: Technically oversee the architecture to identify, describe, and enrich events in historical vehicle logs using Multimodal LLMs.\n Multi-Modal Data Fusion: Oversee the off-board ingestion and fusion of semantic scene descriptions, ego-centric kinematics, and internal autonomy telemetry to create a holistic diagnostic context for LLM inference.\n Prompt Engineering \u0026 Model Integration: Develop structured prompting templates utilizing Contextual Prompting (CP), Chain-of-Thought (CoT), and In-Context Learning (ICL) to evaluate scenarios.\n AI Inference \u0026 Evaluation Scalability: Architect the integration of foundation models into the Metrics Engine (ME), designing efficient cascade filtering and log slice parallelization strategies to scale high-volume LLM inference across simulation and on-road drive logs while managing computational latency and costs.\n AV Performance Metrics Foundations: Define, design, and implement key metrics to evaluate autonomous vehicle performance, such as lane change capability, oscillations, and braking.\n Driving Policy Integration: Deploy and manage a Retrieval-Augmented Generation (RAG) vector database containing codified AV Driving Policies to ground off-board LLM evaluations in specific Operational Design Domains.\n Cross-Functional Technical Leadership: Serve as a technical escalation point and collaborate with Autonomy (Planner, Prediction, Perception) and Systems teams to deliver high-signal, enriched events.\n Advanced Physical AI R\u0026D: Drive the transition toward Direct Vector-LLM Fusion utilizing emerging Physical AI ecosystems and open-weights Vision-Language-Action (VLA) models to process telemetry off-board without text-translation bottlenecks. \n \n What We're Looking For: \n \n 10+ years of professional experience in software engineering, applied AI/ML, or autonomous vehicle systems development.\n Bachelor's degree in Computer Science, Engineering, Robotics, or a related field.\n Proven experience working with Large Language Models (LLMs) and Vision-Language Models (VLMs) for reasoning, parsing, and scene description.\n Experience with parameter-efficient fine-tuning and deploying open-weights models on internal infrastructure.\n Familiarity with local and cloud vector databases, such as LanceDB, for housing output vector embeddings.\n Experience with adversarial scenario generation and closed-loop simulation environments.\n Strong background leveraging software to develop frameworks, libraries, and tools for calculating and aggregating AV performance metrics.\n Strong analytical and problem-solving skills, particularly in the context of complex system performance evaluation.\n Expert-level proficiency in Python and strong understanding of software development principles. \n \n Bonus Points (not required): \n \n Experience working with autonomous vehicle sensor data, including its processing and in","salary_min":200000,"salary_max":275000,"location":"Pittsburgh, PA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"principal","tags":["embeddings","generative-ai","fine-tuning","rag","llm","autonomous-vehicles","cloud","robotics"],"apply_url":"https://motional.com/open-positions/?gh_jid=7799677003#/7799677003","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-09T14:10:03Z","expires_at":"2026-08-14T14:07:59.503144Z","created_at":"2026-07-10T14:05:50.334397Z","updated_at":"2026-07-15T14:07:59.735842Z","company_name":"Motional","company_slug":"motional","company_logo_url":"https://www.google.com/s2/favicons?domain=motional.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/bd8a325e-af13-4567-9c46-1409196e7f88"},{"id":"e651da08-bc17-4c8c-b426-19a46cba7f02","company_id":"41d4f321-d748-4a4e-962f-dd5d23de3e43","title":"Principal Engineer Tech Lead, Embodied AI \u0026 Off-Board Performance Evaluation","slug":"principal-engineer-tech-lead-embodied-ai-off-board-performance-evaluation-65385fb7","description":"Mission Summary: \n Motional is a leading autonomous driving company on a mission to make driverless vehicles a safe, reliable, and accessible reality. Backed by Hyundai Motor Group, Motional is at the forefront of the physical AI revolution. Motional isn’t just building first-of-its-kind technology; we are transforming transportation to create safer streets and more sustainable mobility options.\n The Systems Readiness and Performance team is the crucial bridge between software development and real-world deployment. We are responsible for driving system design, for verifying and validating the autonomy stack, and for defining, measuring, and validating system performance targets. We work closely with stakeholders in autonomy, infrastructure, and operations to build the definitive safety case for the commercial launch of our fully driverless IONIQ 5 robotaxis in Las Vegas later this year.\n We are seeking a talented Principal Engineer to technically oversee the design, development, and deployment of a novel Embodied AI and Large Language Model (LLM)-based monitoring framework for off-board scenario understanding, intelligence evaluation, and root cause analysis. While this role will pioneer future off-board Vision-Language-Action (VLA) integrations for off-board analysis, it requires strong foundations as an Autonomous Vehicle Performance Metrics developer.\n You will lead the creation of a specialized, off-board evaluation layer that consumes AV drive logs and fleet data to automatically infer scenario safety and assess driving intelligence without running live on the vehicle. Your architectural designs will integrate with internal systems to form a complete pipeline that identifies safety incidents, enriches them with structured context, and conducts detailed root cause analysis to provide the Autonomy team with actionable direction. If you are an innovative individual contributor with a passion for overseeing the integration of complex, scalable data pipelines and state-of-the-art Embodied AI frameworks, we encourage you to apply. \n What You'll Be Doing: \n \n Embodied AI \u0026 LLM Framework Oversight: Technically oversee the architecture to identify, describe, and enrich events in historical vehicle logs using Multimodal LLMs.\n Multi-Modal Data Fusion: Oversee the off-board ingestion and fusion of semantic scene descriptions, ego-centric kinematics, and internal autonomy telemetry to create a holistic diagnostic context for LLM inference.\n Prompt Engineering \u0026 Model Integration: Develop structured prompting templates utilizing Contextual Prompting (CP), Chain-of-Thought (CoT), and In-Context Learning (ICL) to evaluate scenarios.\n AI Inference \u0026 Evaluation Scalability: Architect the integration of foundation models into the Metrics Engine (ME), designing efficient cascade filtering and log slice parallelization strategies to scale high-volume LLM inference across simulation and on-road drive logs while managing computational latency and costs.\n AV Performance Metrics Foundations: Define, design, and implement key metrics to evaluate autonomous vehicle performance, such as lane change capability, oscillations, and braking.\n Driving Policy Integration: Deploy and manage a Retrieval-Augmented Generation (RAG) vector database containing codified AV Driving Policies to ground off-board LLM evaluations in specific Operational Design Domains.\n Cross-Functional Technical Leadership: Serve as a technical escalation point and collaborate with Autonomy (Planner, Prediction, Perception) and Systems teams to deliver high-signal, enriched events.\n Advanced Physical AI R\u0026D: Drive the transition toward Direct Vector-LLM Fusion utilizing emerging Physical AI ecosystems and open-weights Vision-Language-Action (VLA) models to process telemetry off-board without text-translation bottlenecks. \n \n What We're Looking For: \n \n 10+ years of professional experience in software engineering, applied AI/ML, or autonomous vehicle systems development.\n Bachelor's degree in Computer Science, Engineering, Robotics, or a related field.\n Proven experience working with Large Language Models (LLMs) and Vision-Language Models (VLMs) for reasoning, parsing, and scene description.\n Experience with parameter-efficient fine-tuning and deploying open-weights models on internal infrastructure.\n Familiarity with local and cloud vector databases, such as LanceDB, for housing output vector embeddings.\n Experience with adversarial scenario generation and closed-loop simulation environments.\n Strong background leveraging software to develop frameworks, libraries, and tools for calculating and aggregating AV performance metrics.\n Strong analytical and problem-solving skills, particularly in the context of complex system performance evaluation.\n Expert-level proficiency in Python and strong understanding of software development principles. \n \n Bonus Points (not required): \n \n Experience working with autonomous vehicle sensor data, including its processing and in","salary_min":200000,"salary_max":275000,"location":"Remote (US)","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"principal","tags":["rag","fine-tuning","robotics","generative-ai","data-pipeline","embeddings","llm","cloud"],"apply_url":"https://motional.com/open-positions/?gh_jid=7799653003#/7799653003","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-09T14:10:01Z","expires_at":"2026-08-14T14:07:59.77536Z","created_at":"2026-07-10T14:05:50.254594Z","updated_at":"2026-07-15T14:07:59.919958Z","company_name":"Motional","company_slug":"motional","company_logo_url":"https://www.google.com/s2/favicons?domain=motional.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/e651da08-bc17-4c8c-b426-19a46cba7f02"},{"id":"badeb1d6-7048-4b26-8dc7-7015a80bf56b","company_id":"d66267b6-f404-410f-9b8e-fe8bbcfcaf1b","title":"Senior Software Engineer - Python and Data Ecosystem","slug":"senior-software-engineer-python-and-data-ecosystem-9f871560","description":"About ClickHouse\n Recognized on the 2025 Forbes Cloud 100 list, ClickHouse is one of the most innovative and fast-growing private cloud companies. With more than 3,000 customers and ARR that has grown over 250 percent year over year, ClickHouse leads the market in real-time analytics, data warehousing, observability, and AI workloads.\n The company’s sustained, accelerating momentum was recently validated by a $400M Series D financing round. Over the past three months, customers including Capital One, Lovable, Decagon, Polymarket, and Airwallex have adopted the platform or expanded existing deployments. These customers join an established base of AI innovators and global brands such as Meta, Cursor, Sony, and Tesla.\n We’re on a mission to transform how companies use data. Come be a part of our journey!\n The Connectors team is the bridge between ClickHouse and the broader data ecosystem. We build and maintain the integrations that make ClickHouse accessible to millions of developers, data practitioners, and AI agents worldwide from high-level data visualization plugins (Tableau, PowerBI, Superset, Metabase) to connectors for data frameworks (Apache Spark, Flink, Kafka Connect, Fivetran), orchestration platforms, and AI tooling.\n Our work directly shapes how companies process massive datasets: real-time analytics platforms ingesting millions of events per second, observability systems monitoring global infrastructure, and increasingly, the AI-powered data applications redefining how teams work with data. We collaborate closely with the open-source community, internal teams, and enterprise users to ensure ClickHouse integrations set the standard for performance, reliability, and developer experience.\n About the role\n As a Senior Software Engineer specializing in Python and the Data Ecosystem , you'll be a core contributor owning and evolving critical parts of ClickHouse's data engineering ecosystem. This role sits at the intersection of high-performance database engineering and developer experience. You'll craft tools that enable Data Engineers and Data Scientists to harness ClickHouse's speed and scale in the frameworks they already use.\n We're looking for someone who has lived the Data Engineer or Data Scientist experience firsthand. The data practitioner's world is shifting rapidly: databases are no longer just query targets, but they're becoming active participants in AI-powered workflows, serving as vector stores for RAG pipelines, backends for LLM-powered agents, and real-time feature stores for ML inference. You understand these workflows not from the outside, but because you've operated within them. You don't just build integrations, you bring product-level insight into what we should build and why.\n You'll own the full lifecycle of key Python integrations, driving architecture, performance, and feature direction across:\n \n Orchestration Platforms: Apache Airflow, Dagster, Prefect\n Transformation Tools: dbt, SQLMesh\n AI \u0026 LLM Ecosystem: LangChain, LlamaIndex, n8n, and broader AI tooling: embedding pipelines, retrieval-augmented generation with ClickHouse as a vector store, ML feature stores, and LLM-powered data applications\n \n ClickHouse's columnar architecture and query performance make it exceptionally well-positioned in this new landscape. Your job is to make that potential real:  building the robust, production-ready connectors that make ClickHouse the natural choice when data practitioners design their next-generation AI and data systems.\n What you'll do \n \n Own and evolve ClickHouse's Python connector and SDK ecosystem, raising the bar on performance, reliability, and API design\n Build and maintain integrations with orchestration platforms (Airflow, Dagster, Prefect) and transformation tools (dbt) to enterprise-grade quality standards\n Drive the AI/LLM integration strategy:  designing connectors and patterns that make ClickHouse a natural fit in RAG architectures, ML feature pipelines, and LLM-powered data applications\n Engage actively with the open-source community: triage issues, support contributors, advocate for users, and shape the roadmap based on real-world feedback\n Collaborate with Product, Cloud, and other engineering teams to align integration work with broader platform priorities\n Bring a practitioner's perspective to roadmap decisions, grounding prioritization in genuine Data Engineer and Data Scientist workflows\n \n About you \n \n 7+ years of software development experience, including hands-on time as a Data Engineer, Data Scientist, or ML Engineer\n Deep, proven experience designing, building, and maintaining production-grade Python connectors, SDKs, or integrations for at least one major platform (orchestration, BI, MLOps, or data transformation)\n Hands-on experience applying AI/ML in production data-engineering contexts: embedding generation, vector search, feature pipelines, or LLM-powered tooling that shipped and ran in production\n Solid experience with the Python data ecosy","salary_min":157000,"salary_max":232000,"location":"United States","workplace":"remote","remote_scope":"restricted","job_type":"full-time","experience_level":"senior","tags":["mlops","embeddings","llm","agents","api-design","healthcare","data-pipeline","rag"],"apply_url":"https://job-boards.greenhouse.io/clickhouse/jobs/6107514004","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-09T12:23:47Z","expires_at":"2026-08-14T14:16:34.442006Z","created_at":"2026-07-09T14:14:22.744462Z","updated_at":"2026-07-15T14:16:34.637848Z","company_name":"ClickHouse","company_slug":"clickhouse","company_logo_url":"https://www.google.com/s2/favicons?domain=clickhouse.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/badeb1d6-7048-4b26-8dc7-7015a80bf56b"},{"id":"26a6c1a9-8651-4f0f-9719-559626bfb1ec","company_id":"ec4a8bb4-3840-4054-8ccd-77e81db037af","title":"Data Scientist/Senior Data Scientist","slug":"data-scientistsenior-data-scientist-8e359427","description":"C3 AI (NYSE: AI), is the Enterprise AI application software company. C3 AI delivers a family of fully integrated products including the C3 Agentic AI Platform, an end-to-end platform for developing, deploying, and operating enterprise AI applications, C3 AI applications, a portfolio of industry-specific SaaS enterprise AI applications that enable the digital transformation of organizations globally, and C3 Generative AI, a suite of domain-specific generative AI offerings for the enterprise. Learn more at: C3 AI \n As a member of the C3 AI Data Science team , you will work with some of the largest companies on the planet helping them build the next generation of AI-powered enterprise applications on the C3 AI Platform. You will work directly with data scientists, AI engineers, and subject matter experts to design and deploy AI capabilities that give our customers the information they need to make better decisions and accelerate their digital transformation. You will identify the right AI approaches for each problem and implement them on the C3 AI Platform so they run reliably at enterprise scale.\n Qualified candidates will have deep knowledge of modern AI and ML techniques — including large language models, agentic systems, and classical statistical methods — along with a clear understanding of their limitations and how to adapt them to large-scale production environments. Some travel is expected.\n Note: This is a client-facing position which requires travel. Candidates should have the ability and willingness to travel based on business needs. \n Responsibilities: \n \n Lead the research, design, implementation, and deployment of AI models, agentic solutions, and optimization algorithms for enterprise applications on the C3 AI Platform.\n Partner with C3 AI customers to build and scale their own AI applications on the Platform.\n Contribute to the design and implementation of new AI capabilities within the C3 AI Platform.\n Analyze model performance across enterprise deployments, diagnose issues such as poor recall or false positive rates, and recommend targeted improvements.\n Collaborate with data engineers and subject matter experts from C3 AI and customer teams to source, validate, and correctly leverage new data assets.\n \n Qualifications: \n \n MS or PhD in Computer Science, Electrical Engineering, Statistics,   Operations Research, or a related field.\n Hands-on AI experience spanning generative AI, agentic systems, supervised and unsupervised learning, and classical regression and classification.\n Strong mathematical foundation in linear algebra, calculus, probability, and statistics.\n Experience building and deploying models at scale in distributed or cloud-native environments.\n Ability to drive projects independently and collaborate effectively across technical and non-technical teams.\n Sharp, motivated, and focused on making a real impact.\n Excellent verbal and written communication skills.\n \n Preferred Qualifications: \n \n Proficiency in Python; experience with JavaScript, Java, or Scala is a plus.\n Familiarity with LLM frameworks (e.g., LangChain, LlamaIndex), vector databases, or RAG architectures.\n A portfolio of AI projects (GitHub, publications, or open-source contributions) is a plus.\n C3 AI provides excellent benefits, a competitive compensation package and generous equity plan. \n California Base Pay Range\n $136,000 — $183,000 USD \n C3 AI is proud to be an Equal Opportunity and Affirmative Action Employer. We do not discriminate on the basis of any legally protected characteristics, including disabled and veteran status.","salary_min":136000,"salary_max":183000,"location":"Redwood City, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["generative-ai","embeddings","agents","llm","rag","data-science"],"apply_url":"https://c3.ai/job-description/8621803002?gh_jid=8621803002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-06T23:21:46Z","expires_at":"2026-08-14T14:11:53.778371Z","created_at":"2026-07-07T14:11:23.526299Z","updated_at":"2026-07-15T14:11:53.901752Z","company_name":"C3 AI","company_slug":"c3-ai","company_logo_url":"https://www.google.com/s2/favicons?domain=c3.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/26a6c1a9-8651-4f0f-9719-559626bfb1ec"},{"id":"035f4105-3142-414e-a11c-a881a475eff5","company_id":"e8dfc4ee-9649-4fd0-9c16-90d38a1954e1","title":"Senior Software Engineer, Machine Learning Infrastructure - Generative AI","slug":"senior-software-engineer-machine-learning-infrastructure-generative-ai-451c5671","description":"About the Team \n DoorDash’s GenAI Platform team sits within Machine Learning Platform and builds the shared infrastructure that helps DoorDash, Wolt, and Deliveroo teams safely bring GenAI-powered products, agents, automation, and personalization to production. Our mission is to increase the velocity of business impact from GenAI. A central pillar of that work is running frontier open-weight LLMs and VLMs (such as GLM, Qwen, Kimi, and DeepSeek) ourselves — real-time GPU serving, high-throughput batch inference, and fine-tuning on autoscaling GPUs — delivering large cost and latency wins (for example, a billion embeddings produced roughly 20× cheaper and visual models served roughly 72% cheaper). We also own core platform surfaces including the LLM Gateway, Agent Gateway, evals infrastructure, guardrails, and cost attribution.\n About the Role \n You will join a small, high-leverage team building production infrastructure for Generative AI at DoorDash, leading the design and architecture of our open-weights model platform spanning inference and fine-tuning: real-time GPU serving, high-throughput batch inference, and model fine-tuning. You’ll set technical direction across model serving and inference engines, fine-tuning and training pipelines, GPU autoscaling and utilization, batch pipelines, backend services, and observability, and mentor engineers as you go. This role is ideal for a senior engineer who enjoys owning ambiguous, high-impact systems and pushing the cost/performance frontier of GPU inference and fine-tuning in a fast-moving technical area where product needs, model capabilities, vendor ecosystems, and cost/performance tradeoffs are evolving quickly.\n You’re excited about this opportunity because you will… \n \n Lead the design of infrastructure that helps DoorDash teams move GenAI ideas from prototype to production, increasing the velocity of business impact from AI across the company.\n Own and evolve our open-weights serving stack — real-time GPU endpoints, high-throughput batch inference, and fine-tuning (SFT/DPO/LoRA) — alongside the LLM Gateway, Agent Gateway, evals infrastructure, guardrails, and cost attribution.\n Architect scalable, high-performance systems for model serving, batch inference, GPU autoscaling, and fine-tuning that power real customer and internal automation use cases\n Push the cost and latency frontier of GPU inference — turning batch jobs that took days into hours and cutting inference cost by multiples — while giving product teams a clean choice across open-weight and closed-source models with reliability, fallback, observability, and cost controls built in.\n Build platforms that support rapid experimentation while meeting production standards for latency, scale, monitoring, SLOs, playbooks, and operational excellence.\n Partner closely with — and raise the technical bar for — ML engineers, product engineers, data scientists, and platform teams across DoorDash, Wolt, and Deliveroo to turn emerging GenAI capabilities into durable platform primitives.\n Set technical direction for the future of DoorDash’s centralized GenAI platform — including emerging directions such as reinforcement learning (RLHF/RLVR), agent optimization, and other post-training and agentic techniques — enabling the next generation of AI-powered products, agents, automation, and personalization.\n \n We’re excited about you because… \n \n B.S., M.S., or PhD. in Computer Science or equivalent\n 6+ years of industry experience in software engineering\n Deep backend engineering fundamentals, especially in Python and distributed systems.\n Track record of designing and owning production services, APIs, data pipelines, or ML infrastructure at scale.\n Experience operating systems in production, including observability, debugging, reliability, incident response, and performance/cost optimization.\n Deep hands-on experience with LLM inference and/or fine-tuning of open-weight models in production — serving (latency, throughput, batching, autoscaling, GPU utilization) and/or fine-tuning (SFT/DPO/LoRA).\n Demonstrated technical leadership: leading design across ambiguous, fast-moving technical areas, mentoring engineers, and turning customer use cases into reusable platform capabilities\n Proficiency in using AI coding tools (e.g., Claude Code, Codex, Cursor) in the full software development lifecycle, including designing, generating code, testing, monitoring and releasing software\n \n Nice To Haves \n \n Experience with LLM inference engines and serving frameworks (e.g., vLLM, SGLang, TensorRT-LLM) in production\n Experience with distributed/multi-node fine-tuning and training pipelines (SFT, DPO/RLHF, LoRA), including data preparation and evaluation\n GPU performance work — multi-node/distributed inference, KV-cache/memory optimization, quantization (FP8/INT8/AWQ/GPTQ), or cold-start/throughput tuning\n Experience with Kubernetes, cloud infrastructure (AWS/GCP), GPUs, serverless/elastic GPU ","salary_min":203500,"salary_max":299300,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["generative-ai","data-pipeline","mlops","healthcare","embeddings","agents","cloud","reinforcement-learning"],"apply_url":"https://job-boards.greenhouse.io/doordashusa/jobs/8044246","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-02T18:10:05Z","expires_at":"2026-08-14T14:21:31.666489Z","created_at":"2026-07-03T14:18:26.394947Z","updated_at":"2026-07-15T14:21:31.80671Z","company_name":"DoorDash","company_slug":"doordash","company_logo_url":"https://www.google.com/s2/favicons?domain=doordash.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/035f4105-3142-414e-a11c-a881a475eff5"},{"id":"a8afbdfb-b21d-4fef-89f9-4641961e6038","company_id":"5d6de1f6-4d6c-463b-8a2b-a5caeadb97b4","title":"Senior Software Engineer, Build","slug":"senior-software-engineer-build-388d7de2","description":"Astronomer empowers data teams to bring mission-critical software, analytics, and AI to life and is the company behind Astro, the industry-leading unified DataOps platform powered by Apache Airflow®. Astro accelerates building reliable data products that unlock insights, unleash AI value, and powers data-driven applications. Trusted by more than 800 of the world's leading enterprises, Astronomer lets businesses do more with their data. To learn more, visit www.astronomer.io http://www.astronomer.io.\n\n\nABOUT THIS ROLE\n\nApache Airflow is one of the most popular open-source data platform tools. It powers the data platforms at nearly every large company and fast-growing startups: Airbnb, Uber, OpenAI, Anthropic, Nike, Capital One, Disney all use Airflow extensively. At Astronomer, we’re the largest contributors to the project and are building commercial products around Airflow to make it easier to use, run, and scale.\n\n\n\nWe’re in a unique position: as the company behind Apache Airflow, we see data as it moves across entire organizations—from raw ingestion to production dashboards, machine learning models, and AI products. Leveraging this vantage point, our R\u0026D team is developing a global context layer for data—an intelligence layer that powers search and discovery, code generation for data and analytics, and automated root cause analysis. LLMs are already quite good at writing Python and SQL code against data platforms; we think this context layer will give them the metadata necessary for data practitioners everywhere to use LLMs effectively.\n\n\n\nAs a Software Engineer on this team, you’ll help design and build this foundation and the applications around it. You’ll work on some of the hardest and most exciting challenges in data—search, information retrieval, and AI for data pracitioners—while collaborating with a small, highly skilled team that values velocity, creativity, and impact. This role sits at the intersection of applied research, software engineering, and product: we think it takes someone who can work across the stack to build, release, and scale products successfully in this space.\n\n\n\nHybrid Work Model: For this role, you will embrace a flexible hybrid work model with at least 3 days per week in our New York City office.\n\n\n\n\n\nWHAT YOU GET TO DO:\n\n - Shape the future of AI for data engineering - build intelligent systems that understand, reason about, and optimize the flow of data across entire organizations.\n\n - Design and engineer the brain of Astronomer’s context layer, crafting components that power data modeling, semantic search, retrieval, and code generation.\n\n - Push the boundaries of applied AI - experiment with LLMs, embeddings, and cutting-edge retrieval techniques to create developer tools that deliver insights to you and our customers.\n\n - Turn research into reality - work side by side with R\u0026D and product teams to bring early AI concepts to life in the product experience.\n\n - Solve high-impact information retrieval and search challenges at a global scale, leveraging Astronomer’s unparalleled visibility into data pipelines across industries.\n\n - Influence the technical vision and architecture for the next generation of AI-driven data products.\n\n - Represent Astronomer in the community - through open-source contributions, technical talks, and publications that showcase our leadership in AI and data innovation.\n\n\n\n\nWHAT YOU BRING TO THE ROLE:\n\n - 5-8 years of software engineering experience with Python or Go\n\n - Empathy for users, and a deep interest in improving the workflows of data professionals.\n\n - Familiarity with early-stage product development; comfortable working with ambiguity in a fast-changing field.\n\n - Experience with LLMs, vector databases, embeddings, or other applied AI areas—or a strong desire to dive in.\n\n - A creative, experimental mindset: you enjoy exploring uncharted areas, validating hypotheses, and learning through iteration.\n\n - Strong collaboration and communication skills—you can explain complex systems clearly to both technical and non-technical audiences.\n\n - A collaborative approach and comfort working in an evolving, research-driven environment where ideas move quickly.\n\n\n\n\nBONUS POINTS IF YOU HAVE:\n\n - A passion for AI systems for data, developer tools, or machine learning infrastructure.\n\n - Familiarity with Apache Airflow or other orchestration tools.\n\n - Demonstrated contributions to open source projects.\n\n - Experience in search, IR, or large-scale data infrastructure.\n\n - Exposure to early-stage startups or R\u0026D organizations where ambiguity is the norm.\n\n - Experience building out agentic systems on top of frontier models.\n\n\n\nThe estimated total compensation for this role ranges from $200,000 - $230,000 based on leveling and geography, along with an equity component and a comprehensive benefits package. This range is merely an estimate; actual compensation may deviate from this range based on skills, experience, and qualificati","salary_min":200000,"salary_max":230000,"location":"New York, NY","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["data-pipeline","llm","code-generation","agents","embeddings","search"],"apply_url":"https://jobs.ashbyhq.com/astronomer/966b6bf1-23d9-4dab-9959-86f4494f4b3e/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-02T16:42:27.695Z","expires_at":"2026-08-14T14:19:31.192935Z","created_at":"2026-07-03T14:16:35.597942Z","updated_at":"2026-07-15T14:19:31.292489Z","company_name":"Astronomer","company_slug":"astronomer","company_logo_url":"https://www.google.com/s2/favicons?domain=astronomer.io\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/a8afbdfb-b21d-4fef-89f9-4641961e6038"},{"id":"5af85b15-4376-400b-a802-2dfc3ba0d49f","company_id":"0fc88a91-688e-421d-917d-4880569dd976","title":"Principal Engineer, Agentic AI Systems","slug":"principal-engineer-agentic-ai-systems-dcc84ac0","description":"About Inflection AI \n Inflection AI is a Public Benefit Corporation empowering people with human-centered, emotionally intelligent AI. We’re shaping the future of AI by combining emotional intelligence (EQ) and raw intelligence (IQ) to elevate people’s potential. Inflection AI created Pi, the world’s first emotionally intelligent AI, to help people work through decisions, emotions, and challenges. Pi is a personal AI agent powered by Inflection AI’s foundation model, proving that AI can be personal, empathetic, and contextually aware.\n About the Role \n We're looking for a hands-on Principal Engineer to lead the architecture and technical direction of Inflection's agentic AI systems. You'll build production AI agents that can reason, retrieve context, use tools, and safely execute complex workflows while driving the design of scalable agent architectures, evaluation frameworks, observability, and reliability systems. Partnering closely with product, design, and engineering, you'll turn ambiguous problems into AI-native experiences, mentor senior engineers, and help establish the technical standards that power the next generation of intelligent agents.\n  \n What You’ll Do \n \n Build production AI agents that can plan, retrieve context, call tools, take actions, and recover from failures.\n Design agent architectures for task decomposition, tool routing, memory, state management, human approval, and safe execution.\n Create evals and observability systems for multi-step task success, tool-call accuracy, hallucination resistance, latency, cost, and failure modes.\n Integrate agents with APIs, databases, SaaS tools, enterprise systems, internal systems, and user-facing workflows.\n Improve reliability through structured outputs, guardrails, fallback paths, monitoring, permissions, auditability, and human-in-the-loop controls.\n Partner with product, design, and engineering teams to turn ambiguous user problems into shipped AI-native features.\n Make pragmatic model and infrastructure choices across proprietary models, open-source models, orchestration frameworks, vector databases, and cloud environments.\n Contribute to technical direction, engineering best practices, and the quality bar for agentic AI systems.\n Own the technical direction of agentic AI systems, provide support and coaching to the team.\n \n What We're Looking For \n \n 10+ years of engineering experience, including 3+ years at staff/principal or equivalent scope, and 2+ years building production-grade agentic or LLM-powered systems used by real customers.\n Strong Python or TypeScript experience.\n Experience building LLM-powered products, AI agents, RAG systems, automation workflows, or model-integrated applications.\n Strong backend engineering fundamentals, including APIs, databases, queues, testing, observability, cloud infrastructure, and deployment.\n Experience with tool/function calling, structured outputs, embeddings, retrieval, prompt design, and model evaluation.\n Strong product judgment and ability to move from ambiguous problem to shipped product quickly.\n Ability to work effectively in a fast-moving environment with ownership, collaboration, and high technical standards.\n Have a bachelor’s degree or equivalent in a related field to the offered position requirements\n \n Nice to Have \n \n Experience with LangGraph, LlamaIndex, OpenAI, Anthropic, Hugging Face, vLLM, or similar tools.\n Experience with agent memory, planning, multi-agent systems, browser automation, workflow automation, or AI copilots.\n Experience building eval pipelines, synthetic test cases, observability, guardrails, or AI safety systems.\n Experience with enterprise SaaS, productivity tools, developer tools, CRM, support, sales, finance, legal, or operations workflows.\n Experience working in early-stage, high-growth, or zero-to-one product environments\n \n Employee Pay Disclosures \n At Inflection AI, we aim to attract and retain the best employees and compensate them in a way that appropriately and fairly values their individual contributions to the company. For this role, Inflection AI estimates a starting annual base salary to fall within the range of $ 400,000.00 to $ 550,000.00 , depending on a candidate’s qualifications and level of experience. This role also includes a meaningful equity component, allowing employees to share in the long-term success of the company. \n Benefits \n Inflection AI values and supports our team’s mental, emotional, financial and physical health. We are focused on building a positive, safe, inclusive and inspiring place to work. Our benefits include: \n \n Robust medical, dental and vision options with employer contributions for HSA, FSA and DFSA\n 401k matching program \n Flexible Time Off, 10 paid holidays, 5 days sick leave\n Parental, Medical and Family care leave \n Generous cell-phone, wellness and office set up stipends \n Support of country-specific visa needs for international employees living in the Bay Area","salary_min":400000,"salary_max":550000,"location":"Palo Alto, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"principal","tags":["rag","alignment","generative-ai","code-generation","agents","cloud","embeddings","llm"],"apply_url":"https://boards.greenhouse.io/inflectionai/jobs/4693056006?gh_jid=4693056006","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-06-29T19:43:43Z","expires_at":"2026-08-14T14:06:37.928565Z","created_at":"2026-06-30T14:04:31.438311Z","updated_at":"2026-07-15T14:06:38.054663Z","company_name":"Inflection AI","company_slug":"inflection-ai","company_logo_url":"https://www.google.com/s2/favicons?domain=inflection.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/5af85b15-4376-400b-a802-2dfc3ba0d49f"},{"id":"19355407-ba64-4d1d-9685-a74fcbe3a19d","company_id":"26618e2f-35c7-42eb-8f60-bd25a7e9a0d2","title":"Staff Software Engineer - AI Platform Team","slug":"staff-software-engineer-ai-platform-team-93d4b769","description":"Ready to do the most impactful work of your career? At  Coinbase , we are uncompromising on our mission to increase economic freedom. The bar is high, the environment is intense, and we like it that way. This isn't a place for complacency, it’s a place to be pushed past your perceived limits. If you're ready to build the future of finance alongside people who refuse to settle for \"good enough,\" you belong here. Coinbase is a remote-first, but not remote-only company. Expect to get together quarterly for intense in-person working sessions called “surges.”  learn more about working at Coinbase .\n As a Staff Software Engineer on the AI Platform team within the Platform  group, you'll build and operate the LLM and agent infrastructure that every team at Coinbase depends on. This team owns the company's single path to large language models and the full agent lifecycle: build, deploy, run, observe, and improve. You'll lead multi-quarter technical initiatives across the platform, from gateway and runtime systems to knowledge bases and applied AI agents, directly shaping how Coinbase scales AI across the organization.\n What you'll do: \n \n Own the architecture and delivery of core platform systems including the LLM Gateway (60+ models, auth, PII redaction, fallbacks, cost optimization), AI Hub, and agent runtime with microVM sandboxes and governed MCP gateway\n Drive the design and implementation of Knowledge Base infrastructure, connecting data sources to auto-provisioned vector and markdown stores queryable by any agent\n Lead AI FinOps capabilities including spend attribution, governance, and cost optimization across all AI workloads company-wide\n Partner across engineering, security, legal, finance, product, and external partners at frontier labs and major cloud providers to ship high-impact platform capabilities\n Build evaluation and observability tooling including LLM-as-judge harnesses, full tracing, and feedback loops that let subject matter experts refine production agents\n Shape applied AI strategy by embedding with teams to build production agents, applying fine-tuning and traditional ML where it outperforms prompting\n \n Required Skills and Experience: \n \n 8+ years of software engineering experience with at least 3 years building ML/AI infrastructure, LLM systems, or distributed platform services at scale\n Demonstrated ability to lead multi-quarter, Staff-level initiatives end-to-end, from technical design through production operation, with measurable platform-wide impact\n Deep expertise in LLM orchestration patterns, agent frameworks, vector databases, and model serving infrastructure across multiple providers\n Proven track record of cross-functional partnership with security, legal, and product teams to ship governed, production-grade AI systems\n Fluency in Python and at least one systems language (Go, Rust, or C++), with production experience building APIs, microservices, and runtime environments\n Utilizes generative AI responsibly, maintaining human oversight to deliver business-ready outputs and drive measurable improvements in workflow efficiency, cost, and quality.\n \n Public Blog Posts: \n \n NodeSmith: AI-Driven Automation for Blockchain Node Upgrades \n Making Smarter Decisions, Faster with AI at Coinbase \n CB-GPT - The opportunity and the vision for GenAI at Coinbase \n Lessons from launching Enterprise-grade GenAI solutions at Coinbase \n AWS re:Invent 2025 - Scaling support, compliance, \u0026 productivity with conversational AI at Coinbase \n \n Job ID#: P76979\n Pay Transparency Notice: Base salary varies by location (see range below). Total compensation may also include equity and bonus eligibility, and benefits (medical, dental, vision, 401(k)). \n  \n Annual base salary range (excluding equity and bonus):\n $218,025 — $256,500 USD \n \n Application Limit: Candidates may submit a maximum of 3 applications within a 6-month period.\n Equal Opportunity Employer: Coinbase is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or genetic information. Applicants with criminal histories will be considered consistent with applicable federal, state, and local laws. \n US Applicants: View Employee Rights , Know Your Rights , and E-Verify Notice of Participation. \n Accommodations: If you are an individual with a disability who needs a reasonable accommodation, email us your request and contact info at accommodations[at]coinbase.com. Need screen reading technology? Click here to download a free compatible screen reader and view the tutorial . \n Data Privacy \u0026 Arbitration: By submitting your application, you agree to our Candidate Privacy Notice . US applicants: By submitting your application, you agree to Arbitration of Disputes .","salary_min":218025,"salary_max":256500,"location":"Remote (US)","workplace":"remote","remote_scope":"restricted","job_type":"full-time","experience_level":"lead","tags":["embeddings","mlops","fine-tuning","agents","cloud","generative-ai","microservices","llm"],"apply_url":"https://www.coinbase.com/careers/positions/8025505?gh_jid=8025505","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-06-24T20:19:53Z","expires_at":"2026-08-14T14:10:59.383574Z","created_at":"2026-06-28T14:08:52.238169Z","updated_at":"2026-07-15T14:10:59.511607Z","company_name":"Coinbase","company_slug":"coinbase","company_logo_url":"https://www.google.com/s2/favicons?domain=www.coinbase.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/19355407-ba64-4d1d-9685-a74fcbe3a19d"},{"id":"343a94a6-ba30-4f9d-b2f5-fc64aba8efea","company_id":"6ce2d21e-b00f-4343-9bd0-5ac62ff81431","title":"Staff Software Engineer, DUE Experience","slug":"staff-software-engineer-due-experience-5a4d5be1","description":"Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states.\n The Driver Understanding and Evaluation (DUE) team at Waymo is developing rich metrics for understanding the behavior of the Waymo Driver in the real world, and technologies such as  context and scene analysis to understand driving, understanding and augmenting real world driving data to generate rare driving events, build large scale data infrastructure, improve components such as agents and a realistic simulator. These technologies come together to drive the overall technical strategy and methodology used to evaluate the behavior of the Waymo Driver. \n You will: \n \n Lead the architectural design and hands-on development of advanced Agentic AI systems, focusing on multi-agent orchestration, tool execution, and complex reasoning loops for event triage.\n Engineer scalable agentic workflows using modern LLM orchestration frameworks to fully automate and augment triage capabilities for Engineering and SWQOps.\n Design and deploy stateful agentic infrastructure, including long-term memory management (RAG, vector databases), semantic routing, and custom internal tool integrations.\n Collaborate with cross-functional partner teams to embed autonomous agents directly into the Waymo Driver evaluation lifecycle.\n Mentor engineers within DUE Experience on agentic development patterns, and prompt engineering\n Tackle broad, ambiguous automation problems by breaking them down into actionable multi-agent projects and leading the technical execution of the roadmap.\n \n You have: \n \n Significant experience (typically 8+ years) in software engineering, with a focus on designing and building large-scale, complex distributed systems.\n Deep expertise in applied LLMs and Agentic AI development, with a proven track record of building multi-agent systems, reasoning engines, and autonomous workflows.\n Strong proficiency with agent orchestration frameworks and advanced prompt engineering.\n Proven ability to execute technical strategy, influence partner teams, and drive end-to-end development of AI-native applications in ambiguous domains.\n Excellent communication and collaboration skills, with the ability to align cross-functional stakeholders on agentic concepts and system limitations.\n Bachelor's degree in Computer Science or a related technical field, or equivalent practical experience.\n \n  \n We prefer: \n \n Master's or PhD in Computer Science or a related field, with a specialization in AI/ML or a related area.\n Experience developing custom tools/plugins for agents, semantic routers, and implementing complex multi-agent collaborative patterns.\n Familiarity with autonomous vehicle simulation, testing, or evaluation domains.\n Proficiency in C++ and Python, with experience building production-grade microservices and pipelines.\n Experience working with large-scale data processing, knowledge graphs, and distributed systems.\n Familiarity with Google's or Waymo's internal AI/ML platforms and infrastructure.\n \n  \n  \n The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process.  \n Waymo employees are also eligible to participate in Waymo’s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements.  \n Salary Range\n $251,000 — $310,000 USD","salary_min":251000,"salary_max":310000,"location":"Mountain View, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["llm","microservices","autonomous-vehicles","embeddings","agents","distributed-systems"],"apply_url":"https://careers.withwaymo.com/jobs?gh_jid=8012269","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-06-22T16:24:45Z","expires_at":"2026-08-14T14:06:32.069887Z","created_at":"2026-06-28T14:04:31.800929Z","updated_at":"2026-07-15T14:06:32.202342Z","company_name":"Waymo","company_slug":"waymo","company_logo_url":"https://www.google.com/s2/favicons?domain=waymo.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/343a94a6-ba30-4f9d-b2f5-fc64aba8efea"},{"id":"21bd2d30-28af-45b9-9102-4144e82d6f4e","company_id":"9a024fe2-b507-4b09-9fd0-f31ed05626e4","title":"AI Agent Engineer, Client Facing","slug":"ai-agent-engineer-client-facing-372df861","description":"About Us \n Observe.AI is the AI Agents platform for customer experience, designed to help organizations deliver faster, smarter, and more efficient customer service at scale. The platform enables businesses to deploy specialized AI Agents that autonomously execute work across the full CX lifecycle—from handling customer conversations to supporting frontline teams and optimizing operations.\n Each AI Agent is purpose-built for a specific role, equipped to understand context, make decisions, take action, and continuously improve outcomes. This allows organizations to increase resolution speed, elevate service quality, and reduce operational costs while empowering your frontline team to focus on higher-value work.\n Built on a CX-native foundation, Observe.AI helps leading brands like DoorDash, Affordable Care, Signify Health, and Verida improve customer satisfaction, boost agent productivity, and deliver consistent, scalable performance across every customer interaction.\n Why Join Us \n We’re looking for an AI Agent Engineer to lead the charge in building and deploying enterprise-grade Voice, Chat AI agents and AI Copilot. This role is hands-on, customer-facing, and pivotal in bringing AI solutions to life - from design and integration to deployment and optimization.\n You’ll own the end-to-end lifecycle of AI Agents: building, integrating, testing, demoing to clients, deploying into production, and tuning performance.\n What You’ll Be Doing \n \n Build \u0026 Deploy Agents : Own the implementation of AI Agents including prompt design, workflow configuration, integrations, telephony setup, and evaluation frameworks.\n Client Engagement: Act as the primary technical partner for customers—lead regular demos, communicate progress, gather feedback, and guide solutions from concept to production.\n Systems Integration: Configure and connect systems using APIs—handling authentication, data mapping, error handling, and integrations with CRMs, knowledge bases, and other enterprise tools.\n Telephony Integration: Set up SIP/CCaaS/PSTN routing, pass metadata, configure fallbacks, and troubleshoot call quality.\n Prompt Design \u0026 Optimization: Write and refine prompts for LLM-driven agents, monitor performance, test iteratively, and ensure agents meet automation and containment targets.\n Strategic Partner: Translate customer requirements into actionable solutions; work consultatively to unblock challenges in security, connectivity, or knowledge ingestion.\n Cross Functional Collaboration: Collaborate with product/engineering teams to escalate platform gaps and resolve deep technical fixes and platformization, while independently driving leading client implementations.\n \n What You’ll Bring To The Role \n \n Bachelor’s degree in Computer Science, Engineering, or a related technical field\n 3+ years in conversational AI, solution engineering, system integration, or delivering AI/LLM-based applications in customer environments, software engineering, or system integration with hands-on delivery of AI/LLM-based solutions.\n Strong ability to communicate and  lead customer-facing discussions - from deep technical troubleshooting to weekly project demos. Ability to explain complex technical concepts to non-technical audiences. \n Must have strong hands-on skills in prompt design, workflow building and API integration (SIP, Twilio, Amazon Connect, etc.).\n Familiarity with LLMs (GPT, Claude, Gemini), vector DBs, and orchestration frameworks (LangChain, LlamaIndex, etc.).\n Working knowledge of retrieval-augmented generation (RAG) concepts, implementation patterns and performance optimization.\n Programming experience in Python, JavaScript, or similar for scripting and integrations\n Strong problem-solving mindset: ability to find workarounds, unblock integrations, and adapt to customer-specific ecosystems. \n Experience with integration tools and Integration Platform-as-a-Service (iPaaS) providers, such as n8n, Zapier, or similar platforms and proficiency in API integrations and data flow management is a plus.\n Familiarity with telephony or voice systems (SIP, CCaaS, PSTN) is a plus. \n \n Why You’ll Love It Here   \n \n Competitive compensation including equity: Market-aligned base pay, performance incentives, and meaningful equity ownership\n Excellent medical, dental, and vision insurance options: Comprehensive medical, dental and vision benefits for employees and eligible dependents\n Flexible Paid Time Off: Our unlimited, flexible PTO policy empowers you to take the time you need to recharge, maintain balance, and perform at your best.\n Additional Time to Recharge: 10 company holidays, an annual company-wide Winter Break, and paid parental leave to fully support life outside of work.\n 401(k) plan: Long-term financial planning support with tax-advantaged retirement savings\n Quarterly Lifestyle Spending Account: Flexible quarterly stipend to support wellness, learning and professional development, and personal growth\n Monthly Mobile + I","salary_min":108000,"salary_max":170000,"location":"Redwood City, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"mid","tags":["code-generation","rag","embeddings","llm","agents","generative-ai","cloud"],"apply_url":"https://www.observe.ai/position?gh_jid=5254531008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-06-12T23:13:49Z","expires_at":"2026-08-14T14:07:22.227093Z","created_at":"2026-06-28T14:05:19.458685Z","updated_at":"2026-07-15T14:07:22.369788Z","company_name":"Observe AI","company_slug":"observe-ai","company_logo_url":"https://www.google.com/s2/favicons?domain=observe.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/21bd2d30-28af-45b9-9102-4144e82d6f4e"},{"id":"3c51bb5a-7527-4bdd-b62f-68a131743e8b","company_id":"9d70a126-16ff-4f5c-9f36-2133735865d3","title":"Staff Data Engineer","slug":"staff-data-engineer-2d95d923","description":"Who We Are \n Verkada is transforming how organizations protect their people and places with an integrated, privacy-sensitive AI-powered platform that includes solutions for video security, access control, air quality sensors, alarms, intercoms, and visitor management. \n We’ve got serious momentum in the market: more than 30,000 customers (including 100+ of the Fortune 500), a $5.8B valuation , more than $1 billion in annualized bookings, and backing from CapitalG, Sequoia Capital, General Catalyst, Felicis Ventures, Next47 and more. Physical AI is one of the most consequential technology shifts of our time, and Verkada is at the center of it.\n You can look at all kinds of communities to see our platform’s impact in the world. It's the retailer that uses our agentic AI to deter theft before it happens. The warehouse that uses AI-powered alerts to make sure its team is protected on the floor with proper PPE. The school that’s alerted to a threat in real-time and triggers a lockdown in seconds, not minutes. We’re rapidly scaling this impact: today, more than 2 million Verkada devices are deployed across 170+ countries. \n About the Role \n As a member of our Data Platforms and Analytics Team and reporting directly to the Head of Data, you will be responsible for developing the core enterprise data warehouse infrastructure, data models, and pipelines at Verkada. We aim to provide a single reporting source of truth for enterprise data with clear business data definitions to empower internal Finance, Sales, Marketing, Product and HR teams to make informed data driven decisions. Our strategy emphasizes automation, scalable architecture, and accuracy, while providing iterative improvements over time.\n We are committed to a thriving in-office culture. This role requires you to be onsite at our HQ in San Mateo, CA.\n What You'll Do \n \n Architect, engineer and maintain efficient, scalable warehouse infrastructure that facilitates high-quality, accurate insights and reporting.\n Lead, design, implement and manage automated data pipelines from various data sources including databases, API endpoints, business systems, and data lakes.\n Lead collaboration across departments to develop bronze, silver, and gold data models, enforcing business alignment and data governance.\n Partner with Finance, Sales, Marketing, Product, and HR stakeholders to define data pipeline sources, data modeling requirements, and data quality standards.\n Partner with the Head of Data to build and drive the data engineering roadmap — translating business priorities, technical debt, and platform gaps into a sequenced, milestone-driven plan that aligns with business objectives.\n Own the entire project lifecycle, moving initiatives from initial design through to production leveraging development standards such as Github PR reviews and Jira sprint board management.\n Drive platform-wide engineering standards: code quality, testing frameworks, CI/CD practices, data modeling conventions, and documentation, raising the bar across the entire data engineering team.\n Create and deploy strategies to maintain data security, integrity, and regulatory compliance.\n Provide leadership and guidance to grow and mentor future members of the data engineering team.\n \n What You Bring \n \n Bachelor's or Master's degree in Computer Science or a related technical field.\n Minimum of 10 years of professional data engineering experience.\n Advanced skill in Python and SQL.\n Expertise with cloud warehouses such as BigQuery, Snowflake, or Databricks leveraging DBT as a data modeling framework.\n Expertise in managing data lakes with open source file formats such as Apache Iceberg, Delta Lake or Apache Hudi\n Proven track record in constructing automated pipelines using Airflow, Dagster, Fivetran from various operational databases, API endpoints, business systems, and data lakes.\n Expert-level proficiency in SQL and Python is required.\n Experience building / managing data observability and data quality platforms such as BigEye, Monte Carlo and Great Expectations is a plus\n Familiarity or experience building vector databases for Generative AI use cases is a plus.\n Experience building Gen AI agents to optimize development workflows within data engineering is a plus.\n Experience building Gen AI agents for providing support for business intelligence related inquiries is a plus\n Must be willing and able to work onsite five days per week.\n \n Employee Benefits \n Verkada is committed to fostering a workplace environment that prioritizes the holistic health and wellbeing of our employees and their families by offering comprehensive wellness perks, benefits, and resources. Our benefits and perks programs include, but are not limited to:\n \n Healthcare programs that can be tailored to meet the personal health and financial well-being needs - Premiums are 100% covered for the employee under at least one plan and 80% for family premiums under all plans\n Nationwide medical, vision and dental ","salary_min":190000,"salary_max":250000,"location":"San Mateo, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["agents","healthcare","data-pipeline","embeddings","generative-ai","data-engineering"],"apply_url":"https://job-boards.greenhouse.io/verkada/jobs/5162794007","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-06-12T18:07:21Z","expires_at":"2026-08-14T14:11:46.455573Z","created_at":"2026-06-28T14:09:27.17647Z","updated_at":"2026-07-15T14:11:46.583047Z","company_name":"Verkada","company_slug":"verkada","company_logo_url":"https://www.google.com/s2/favicons?domain=verkada.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/3c51bb5a-7527-4bdd-b62f-68a131743e8b"},{"id":"8352f711-7331-4dc7-86f0-63e0d4174f39","company_id":"b4787255-dacd-444b-8e44-bb9971ec1f36","title":"Principal Software Engineer (GTMO/Mesh)","slug":"principal-software-engineer-gtmomesh-b3cea78f","description":"ZoomInfo is where careers accelerate. We move fast, think boldly, and empower you to do the best work of your life. You’ll be surrounded by teammates who care deeply, challenge each other, and celebrate wins. With tools that amplify your impact and a culture that backs your ambition, you won’t just contribute. You’ll make things happen–fast.\n Mesh is ZoomInfo's internal AI platform. Thousands of employees use it every day — to run AI agents, build automated workflows, create microapps, and connect to the tools they already work in. It's a platform with a lot of moving parts, and a small engineering team that owns all of them.\n We're looking for a Principal Software Engineer who raises the bar on how we ship, not just what we ship.\n What you'll be doing: \n \n Owning features across the full stack — React frontends, backend APIs, cloud infrastructure — from design through production\n Responding to production incidents and shipping fixes\n Building and improving core platform capabilities: AI agents, orchestration workflows, microapp infrastructure, LLM integrations\n Developing SDKs and tooling for engineers who build on top of Mesh\n Championing quality and reliability — tests, coverage, habits that prevent regressions\n Collaborating across teams and supporting users directly through our Slack support channels\n Mentoring engineers through code reviews and technical guidance\n \n Why Mesh: \n \n Small team, real impact — your contributions are visible and your opinions carry weight\n We use AI tools heavily in our own workflow — Claude Code, AI-assisted code review, LLM-powered automation\n Distributed systems, LLM reliability, workflow orchestration, real-time integrations — the problems are hard and varied\n We move fast and we're getting smarter about how we do it\n \n What you'll bring: \n \n 12+ years of software engineering experience with a track record of delivering reliable, scalable systems\n Strong full-stack skills — React/TypeScript, backend services, cloud infrastructure\n Experience building in a cloud-native environment, preferably GCP — Kubernetes, Cloud Functions, Pub/Sub, managed databases\n Solid understanding of SQL and NoSQL databases — Postgres, MongoDB, Redis\n Experience owning production systems — logs, incident triage, fixes under pressure\n A real commitment to software quality — testing strategy, code review, regression prevention\n Security awareness built into how you work\n You disagree and commit — push back when something is wrong, but don't relitigate once a decision is made\n Clear communication and experience in fast-moving, high-ownership environments\n \n Preferred: \n \n Experience with LLMs — Claude, GPT, Llama — and building applications on top of them\n Familiarity with context engineering and RAG patterns\n Experience with MCP or AI tool integrations\n Experience with Temporal or similar workflow orchestration systems\n Experience with vector databases — Pinecone, pgvector, etc.\n Experience building developer-facing SDKs or platform tooling\n Experience with CI/CD pipelines, particularly GitHub Actions\n \n \n #LI-AR2 \n #LI-Remote \n Actual compensation offered will be based on factors such as the candidate’s work location, qualifications, skills, experience and/or training. Your recruiter can share more information about the specific salary range for your desired work location during the hiring process. We want our employees and their families to thrive.\n In addition to comprehensive benefits we offer holistic mind, body and lifestyle programs designed for overall well-being. Learn more about ZoomInfo benefits here .\n Below is the US base salary for this position. Additional compensation such as Bonus, Commission, Equity and other benefits may also apply.\n $163,800 — $257,400 USD \n About us:  \n ZoomInfo (NASDAQ: GTM) is the Go-To-Market Intelligence Platform that empowers businesses to grow faster with AI-ready insights, trusted data, and advanced automation. Its solutions provide more than 35,000 companies worldwide with a complete view of their customers, making every seller their best seller.\n ZoomInfo is committed to protecting your privacy when you apply for jobs with us. Please review our Job Applicant Privacy Notice for more details on how we handle your personal information.\n ZoomInfo may use a software-based assessment as part of the recruitment process. More information about this tool, including the results of the most recent bias audit, is available here .\n ZoomInfo is proud to be an equal opportunity employer, hiring based on qualifications, merit, and business needs, and does not discriminate based on protected status. We welcome all applicants and are committed to providing equal employment opportunities regardless of sex, race, age, color, national origin, sexual orientation, gender identity, marital status, disability status, religion, protected military or veteran status, medical condition, or any other characteristic protected by applica","salary_min":163800,"salary_max":257400,"location":"Remote (US)","workplace":"remote","remote_scope":"restricted","job_type":"full-time","experience_level":"principal","tags":["cloud","agents","llm","distributed-systems","embeddings","rag"],"apply_url":"https://www.zoominfo.com/careers?gh_jid=8574368002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-06-11T14:52:06Z","expires_at":"2026-08-14T14:21:19.386453Z","created_at":"2026-06-28T14:17:56.55036Z","updated_at":"2026-07-15T14:21:19.497533Z","company_name":"ZoomInfo","company_slug":"zoominfo","company_logo_url":"https://www.google.com/s2/favicons?domain=zoominfo.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/8352f711-7331-4dc7-86f0-63e0d4174f39"},{"id":"f2dcab5e-6bb0-49c6-9cc2-435cd103e988","company_id":"26618e2f-35c7-42eb-8f60-bd25a7e9a0d2","title":"Senior Software Engineer - AI Platform Team","slug":"senior-software-engineer-ai-platform-team-0ab7579c","description":"Ready to do the most impactful work of your career? At  Coinbase , we are uncompromising on our mission to increase economic freedom. The bar is high, the environment is intense, and we like it that way. This isn't a place for complacency, it’s a place to be pushed past your perceived limits. If you're ready to build the future of finance alongside people who refuse to settle for \"good enough,\" you belong here. Coinbase is a remote-first, but not remote-only company. Expect to get together quarterly for intense in-person working sessions called “surges.”  learn more about working at Coinbase .\n As a Senior Software Engineer on the AI Platform team within the Platform group, you'll build and operate the LLM and agent infrastructure that every team at Coinbase depends on. This team owns the company's single path to large language models and the full agent lifecycle: build, deploy, run, observe, and improve. You'll lead multi-quarter technical initiatives across the platform, from gateway and runtime systems to knowledge bases and applied AI agents, directly shaping how Coinbase scales AI across the organization.\n What you'll do: \n \n Own the architecture and delivery of core platform systems including the LLM Gateway (60+ models, auth, PII redaction, fallbacks, cost optimization), AI Hub, and agent runtime with microVM sandboxes and governed MCP gateway\n Drive the design and implementation of Knowledge Base infrastructure, connecting data sources to auto-provisioned vector and markdown stores queryable by any agent\n Lead AI FinOps capabilities including spend attribution, governance, and cost optimization across all AI workloads company-wide\n Partner across engineering, security, legal, finance, product, and external partners at frontier labs and major cloud providers to ship high-impact platform capabilities\n Build evaluation and observability tooling including LLM-as-judge harnesses, full tracing, and feedback loops that let subject matter experts refine production agents\n Shape applied AI strategy by embedding with teams to build production agents, applying fine-tuning and traditional ML where it outperforms prompting\n \n Required Skills and Experience: \n \n 5+ years of software engineering experience with demonstrated expertise building ML/AI infrastructure, LLM systems, or distributed platform services at scale\n Demonstrated ability to lead multi-quarter initiatives end-to-end, from technical design through production operation, with measurable platform-wide impact\n Deep expertise in LLM orchestration patterns, agent frameworks, vector databases, and model serving infrastructure across multiple providers\n Proven track record of cross-functional partnership with security, legal, and product teams to ship governed, production-grade AI systems\n Fluency in Python and at least one systems language (Go, Rust, or C++), with production experience building APIs, microservices, and runtime environments\n Utilizes generative AI responsibly, maintaining human oversight to deliver business-ready outputs and drive measurable improvements in workflow efficiency, cost, and quality.\n \n Public Blog Posts: \n \n NodeSmith: AI-Driven Automation for Blockchain Node Upgrades \n Making Smarter Decisions, Faster with AI at Coinbase \n CB-GPT - The opportunity and the vision for GenAI at Coinbase \n Lessons from launching Enterprise-grade GenAI solutions at Coinbase \n AWS re:Invent 2025 - Scaling support, compliance, \u0026 productivity with conversational AI at Coinbase \n Pay Transparency Notice: Base salary varies by location (see range below). Total compensation may also include equity and bonus eligibility, and benefits (medical, dental, vision, 401(k)). \n  \n Annual base salary range (excluding equity and bonus):\n $186,065 — $218,900 USD \n \n Application Limit: Candidates may submit a maximum of 3 applications within a 6-month period.\n Equal Opportunity Employer: Coinbase is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or genetic information. Applicants with criminal histories will be considered consistent with applicable federal, state, and local laws. \n US Applicants: View Employee Rights , Know Your Rights , and E-Verify Notice of Participation. \n Accommodations: If you are an individual with a disability who needs a reasonable accommodation, email us your request and contact info at accommodations[at]coinbase.com. Need screen reading technology? Click here to download a free compatible screen reader and view the tutorial . \n Data Privacy \u0026 Arbitration: By submitting your application, you agree to our Candidate Privacy Notice . US applicants: By submitting your application, you agree to Arbitration of Disputes .","salary_min":186065,"salary_max":218900,"location":"Remote (US)","workplace":"remote","remote_scope":"restricted","job_type":"full-time","experience_level":"senior","tags":["embeddings","generative-ai","microservices","llm","fine-tuning","mlops","agents","cloud"],"apply_url":"https://www.coinbase.com/careers/positions/7997420?gh_jid=7997420","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-06-10T19:30:20Z","expires_at":"2026-08-14T14:10:59.04281Z","created_at":"2026-06-28T14:08:51.868011Z","updated_at":"2026-07-15T14:10:59.175405Z","company_name":"Coinbase","company_slug":"coinbase","company_logo_url":"https://www.google.com/s2/favicons?domain=www.coinbase.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/f2dcab5e-6bb0-49c6-9cc2-435cd103e988"},{"id":"f8a2299a-003d-4a9e-9b6d-4fb5ee6b9c23","company_id":"d8e15a46-b80d-4228-8e7b-34f00357f377","title":"Principal Search Consulting Architect","slug":"principal-search-consulting-architect-38429fa6","description":"Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale — unleashing the potential of businesses and people. The Elastic Search AI Platform, used by more than 50% of the Fortune 500, brings together the precision of search and the intelligence of AI to enable everyone to accelerate the results that matter. By taking advantage of all structured and unstructured data — securing and protecting private information more effectively — Elastic’s complete, cloud-based solutions for search, security, and observability help organizations deliver on the promise of AI.\n What is the Role \n As a Principal Search Architect , you will serve as the elite technical authority and visionary leader helping our largest enterprise customers unlock the full potential of Elasticsearch . Acting as a strategic, trusted advisor to CTOs and Enterprise Architecture teams, you will design, govern, and scale massive, complex Elasticsearch cluster topologies that transform application search performance, data retrieval infrastructure, and AI-powered semantic search capabilities.\n You will bridge the gap between business strategy and cutting-edge distributed systems engineering, collaborating directly with Elastic’s global Professional Services leadership, Core Engineering, Product Management, and Sales executives. In this high-impact role, you will shape the future of enterprise deployments by driving regional architectural standards, leading critical cluster migrations, and mentoring both Fortune 500 engineering teams and internal Elastic technical staff.\n What You Will Be Doing \n \n Elasticsearch Core Architecture: Translate highly complex business requirements into resilient, next-generation enterprise retrieval architectures built natively on distributed Elasticsearch environments.\n Cluster Governance \u0026 Design: Lead the overarching technical strategy and design authority for high-stakes customer engagements—from initial node blueprinting and capacity planning to custom mappings, shard strategy, Index Lifecycle Management (ILM), and cross-cluster replication (CCR/CCS).\n Advanced Vector Search \u0026 AI Engineering: Design and operationalize cutting-edge semantic search architectures utilizing Elasticsearch’s native vector database capabilities, including kNN, Approximate Nearest Neighbor (ANN), ELSER (Elastic Learned Sparse Encoder), hybrid retrieval, and Retrieval-Augmented Generation (RAG) pipelines.\n Performance Tuning \u0026 Optimization: Profile, benchmark, and tune distributed search and indexing performance for ultra-high-QPS environments with aggressive sub-second SLAs, optimizing Apache Lucene segment merging, caching layers, and heap/garbage collection configurations.\n High-Throughput Indexing: Architect robust distributed ingestion strategies handling petabyte-scale throughput, optimizing cluster state performance, thread pools, and bulk indexing requests for maximum efficiency.\n Cross-Functional Influence: Collaborate cross-functionally with Elastic Product Management and Core Engineering to influence the Elasticsearch codebase roadmap, surface edge-case bugs, and drive feature enhancement requests based on enterprise field realities.\n Community \u0026 IP Development: Capture, formalize, and publish global best practices, reference architectures, and reusable solution patterns across the broader Elasticsearch and open-source engineering communities.\n Culture of Excellence: Drive internal enablement initiatives, mentor senior engineers, and cultivate a culture of continuous technical excellence and deep mastery of Elasticsearch internals.\n \n What You Bring \n \n 8+ years as a Principal Architect, Lead Engineer, or Senior Systems Consultant with recognized, deep technical expertise specifically focused on Elasticsearch at a massive scale.\n Elasticsearch Internals Mastery: Comprehensive understanding of distributed systems theory as it applies to Elasticsearch, including consensus protocols, internal node roles (master, data, ingest, machine learning), Apache Lucene indexing mechanics, and cluster state management.\n AI-Powered Search Expertise: Proven track record of deploying production-grade semantic search solutions using Elasticsearch’s native ML nodes, dense/sparse vector fields, and integrations with modern NLP frameworks and LLM orchestration tools.\n Cloud-Native Infrastructure: Advanced knowledge of orchestrating massive Elasticsearch workloads across cloud platforms (AWS, Azure, GCP) using cloud-native patterns, Docker, and Terraform.\n Polyglot Coding: Strong proficiency in multiple programming languages (e.g., Java, Python, Go) with extensive experience utilizing official Elasticsearch client libraries and building custom plugins.\n Elite Communication: Exceptional presentation and storytelling skills, with verified experience commanding a room of executive stakeholders to align technical Elasticsearch roadmaps with core business strategy.\n Education: Ba","salary_min":191900,"salary_max":303500,"location":"United States","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"principal","tags":["nlp","search","rag","embeddings","llm","distributed-systems"],"apply_url":"https://jobs.elastic.co/jobs?gh_jid=7988387\u0026gh_jid=7988387","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-06-08T21:02:33Z","expires_at":"2026-08-14T14:10:51.603248Z","created_at":"2026-06-28T14:08:43.714248Z","updated_at":"2026-07-15T14:10:51.752768Z","company_name":"Elastic","company_slug":"elastic","company_logo_url":"https://www.google.com/s2/favicons?domain=www.elastic.co\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/f8a2299a-003d-4a9e-9b6d-4fb5ee6b9c23"},{"id":"e3989b5d-4d67-4c21-8114-ea0ebd9d404f","company_id":"2721f049-2cf2-4e3e-82d0-8d8df89c8f90","title":"Forward Deployed Engineer, Enterprise - Tavily","slug":"forward-deployed-engineer-enterprise-tavily-e55656da","description":"About Nebius: \n Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure.\n Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI.\n Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R\u0026D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R\u0026D.\n About Tavily \n We're building the search engine for AI agents. Our API powers agentic applications and real-time reasoning by connecting LLMs to high-quality, trustworthy web content. We work with some of the most innovative teams in AI — from startups shaping the ecosystem to enterprises deploying AI at scale. \n The Team\n Forward Deployed Engineering owns how Tavily shows up technically in the field. The team sits at the intersection of customers, Product, Engineering, Sales, Partnerships, and Customer Success. \n The Enterprise FDE motion focuses on Tavily’s highest-value customers and strategic enterprise opportunities — from technical discovery and solution design through proof of concept, production rollout, adoption, and expansion. \n The role \n This is a full-time, on-site role based in our New York office. \n As a Forward Deployed Engineer, Enterprise, you’ll work directly with Tavily’s largest and most strategic customers to design, prototype, and deploy production-grade AI systems powered by Tavily’s API. You’ll own the technical relationship across the customer lifecycle, helping enterprise teams move from early use case exploration to deployed, scalable agentic applications. \n You’ll be deeply hands-on: building RAG pipelines, agent workflows, evaluation loops, reference architectures, and custom integrations alongside customer teams. You’ll also serve as a critical bridge between the field and our Product and Engineering teams, translating enterprise needs into roadmap signal. \n Your responsibilities will include:   \n \n Work directly with enterprise customers to understand their AI use cases, technical architecture, success criteria, and deployment requirements. \n Lead technical discovery and solution design during pre-sales and expansion conversations. \n Scope, build, and deliver proofs of concept that demonstrate clear business and technical value. \n Design and implement production-ready integrations using Tavily’s API, including RAG pipelines, agent workflows, internal tools, and industry-specific GenAI applications. \n Partner with customer engineering, data, product, and AI teams to move use cases from prototype to production. \n Monitor customer API usage patterns and recommend improvements to increase reliability, latency, coverage, and overall value. \n Translate recurring customer needs, blockers, and technical patterns into clear product and roadmap input. \n Create reusable enterprise assets, including reference architectures, integration templates, deployment guides, demo environments, and technical documentation. \n Represent Tavily in customer architecture reviews, executive technical conversations, implementation check-ins, and post-deployment reviews. \n Partner closely with Sales, Customer Success, Product, and Engineering to drive adoption, retention, and expansion across strategic accounts. \n \n We expect you to have:   \n \n 3+ years of software engineering experience, ideally in a customer-facing technical role such as Forward Deployed Engineer, Solutions Architect, Solutions Engineer, Sales Engineer, or Technical Consultant. \n Strong hands-on engineering ability, especially with Python, APIs, backend systems, and production software development. \n Experience building with LLMs, Retrieval-Augmented Generation, agent architectures, context engineering, and modern AI application stacks. \n Experience working with enterprise customers, including technical discovery, POCs, solution design, stakeholder management, and production rollout. \n Strong understanding of how enterprises evaluate, deploy, secure, and scale AI systems. \n Ability to communicate clearly with both technical and executive stakeholders, including engineering leaders, product teams, AI teams, and technical decision-makers. \n High autonomy, strong ownership, and comfort operating in a fast-moving startup environment. \n Excellent written and verbal communication skills, with the ability to turn complex technical concepts into clear recommendations. \n Based in New York City, or willing to relocate. \n \n It will be an added bonus if you have:   \n \n Experience working with major agent or LLM orchestration frameworks such as LangChain, Lla","salary_min":179500,"salary_max":224300,"location":"New York, NY","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["rag","embeddings","agents","search","cloud","generative-ai","llm","fine-tuning"],"apply_url":"https://careers.nebius.com/?gh_jid=4880295101","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-06-05T13:35:22Z","expires_at":"2026-08-14T14:17:11.622819Z","created_at":"2026-06-28T14:14:18.105067Z","updated_at":"2026-07-15T14:17:11.728043Z","company_name":"Nebius","company_slug":"nebius","company_logo_url":"https://www.google.com/s2/favicons?domain=nebius.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/e3989b5d-4d67-4c21-8114-ea0ebd9d404f"},{"id":"784c77a7-bf9e-4530-b1e4-01579e0125b3","company_id":"adc4981a-d4ff-4939-952f-362f51e1291d","title":"Sr. Data Scientist","slug":"sr-data-scientist-8c1c1a90","description":"Our Mission: \n 6sense's mission is to multiply what matters: growth, retention, and efficiency.  We envision a future where companies, teams and people reach their full potential.\n Our People: \n People are the heart and soul of 6sense. We serve with passion and purpose. We live by our Being 6sense values of Win as One Team, Stay Curious, Do The Right Thing, Own the Outcome, and Create Belonging.  Every 6sensor plays a part in defining the future of our industry-leading technology.  6sense is a place where difference-makers roll up their sleeves, take risks, act with integrity, and measure success by the value we create for our customers.  We want 6sense to be the best chapter of your career. \n About 6sense\n 6sense is revolutionizing how B2B organizations create, manage, and convert pipeline to revenue. Powered by AI, big data, and predictive analytics, our platform helps revenue teams identify buying intent, engage the right accounts, and drive growth.\n The Opportunity\n We're looking for a Senior Data Scientist (IC4) to join our growing AI and Data Science team. This is an exciting opportunity for an experienced ML practitioner who enjoys building production-grade AI systems and transforming cutting-edge research into impactful customer-facing products.\n You will work on advanced machine learning, NLP, LLMs, Agentic AI, and GenAI applications that directly influence product innovation and customer outcomes.\n What You'll Do\n \n Design, build, and deploy scalable machine learning and AI solutions in production environments.\n Develop NLP and transformer-based systems for enterprise-scale applications.\n Build Agentic AI workflows leveraging frameworks such as LangGraph and LangChain.\n Own the end-to-end ML lifecycle, including:\n \n Data exploration\n Feature engineering\n Model development\n Evaluation\n Deployment\n Monitoring\n \n Develop ranking, recommendation, classification, prediction, and optimization models.\n Partner closely with Product, Engineering, and Analytics teams to solve complex business problems.\n Improve performance, scalability, reliability, and observability of production ML systems.\n Contribute to AI platform architecture and technical strategy.\n Mentor engineers and help elevate engineering excellence across the organization.\n \n What We're Looking For\n Required Qualifications\n \n 8+ years of experience building and deploying machine learning solutions in production.\n Strong foundation in Machine Learning, Statistics, and Applied Data Science.\n Experience with:\n \n Supervised \u0026 Unsupervised Learning\n Recommendation Systems\n Ranking Models\n Predictive Modeling\n \n Deep expertise in:\n \n NLP\n Transformers\n Embeddings\n Encoder-Decoder Architectures\n Retrieval-based Systems\n \n Hands-on experience with GenAI ecosystems including:\n \n LangGraph\n LangChain\n Amazon Bedrock\n \n Strong Python programming skills.\n Experience building distributed ML systems and pipelines using AWS and Databricks.\n Strong understanding of feature engineering, model evaluation, and MLOps.\n Ability to independently solve ambiguous problems and drive execution.\n Strong product mindset with focus on customer impact and business outcomes.\n \n Preferred Qualifications\n \n Experience building Agentic AI and Multi-Agent Systems.\n Experience with:\n \n RAG Architectures\n Vector Databases\n Prompt Engineering\n \n Hands-on experience with PyTorch and/or TensorFlow.\n Prior experience in B2B SaaS or customer-facing AI products.\n \n Base Salary Range: $162,923.67 - $238,954.71 . The base salary range represents the anticipated low and high end of the base salary range for this position. Actual salaries may vary and may be above or below the range based on various factors, including but not limited to work location and experience. The base salary is one component of 6sense’s total compensation package for this position. Other compensation may include a bonus program or commission plan, and stock options if approved by 6sense’s board. In addition, 6sense provides a variety of benefits, including generous health insurance coverage, life, and disability insurance, a 401K employer matching program, paid holidays, self-care days, and paid time off (PTO). #Li-remote \n Notice of Collection and Use of Personal Information for California Residents: California Recruitment Privacy Notice and Policy \n Our Benefits:   \n Full-time employees can take advantage of health coverage, paid parental leave, generous paid time-off and holidays, quarterly self-care days off, and stock options. We’ll make sure you have the equipment and support you need to work and connect with your teams, at home or in one of our offices.  \n We have a growth mindset culture that is represented in all that we do, from onboarding through to numerous learning and development initiatives including access to our LinkedIn Learning platform. Employee well-being is also top of mind for us. We host quarterly wellness education sessions to encourage self care and personal growth. From welln","salary_min":162923,"salary_max":238954,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["llm","generative-ai","tensorflow","nlp","mlops","cloud","embeddings","agents"],"apply_url":"https://boards.greenhouse.io/6sense/jobs/7974951?gh_jid=7974951","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-06-03T13:14:21Z","expires_at":"2026-08-14T14:12:55.691269Z","created_at":"2026-06-28T14:10:27.112574Z","updated_at":"2026-07-15T14:12:55.801285Z","company_name":"6sense","company_slug":"6sense","company_logo_url":"https://www.google.com/s2/favicons?domain=6sense.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/784c77a7-bf9e-4530-b1e4-01579e0125b3"}],"market_demand_pack":{"amount_cents":2900,"api_checkout_url":"https://aidevboard.com/api/v1/checkout?product_id=aidevboard_ai_skills_demand_pack","checkout_url":"https://aidevboard.com/market-demand-pack?qc=api-jobs-market-demand-pack\u0026utm_campaign=skills_demand_pack\u0026utm_medium=jobs_api\u0026utm_source=api","currency":"USD","description":"Full ranked public AI/ML demand CSV, source job URLs, and decision brief with market and offer angles.","fulfillment":"automatic_email_after_paid_checkout","human_checkout_url":"https://aidevboard.com/market-demand-pack?qc=api-jobs-market-demand-pack\u0026utm_campaign=skills_demand_pack\u0026utm_medium=jobs_api\u0026utm_source=api","name":"AI Market Demand Pack","next_step":"Open checkout_url for Stripe Checkout, or call api_checkout_url to get the non-charging checkout handoff payload.","price_usd":29,"product_id":"aidevboard_ai_skills_demand_pack","quote_url":"https://aidevboard.com/api/v1/quote?product_id=aidevboard_ai_skills_demand_pack"},"page":1,"per_page":20,"total":303,"total_pages":16}