{"access":{"advertiser_pricing_url":"https://aidevboard.com/pricing","catalog_url":"https://aidevboard.com/api/v1/catalog","description":"Public read endpoints are open and free. 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We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there.  \n A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone. \n Why Safety AI Systems? \n As Senior Engineering Manager for Safety AI Systems at Roblox, you'll lead technical efforts and manage a team of experienced engineers to develop innovative AI solutions for multimodal content safety. You’ll oversee machine learning systems, constructing multimodal model architectures, improving data quality, training pipelines, and model performance to address challenges like real-time multi-verse content understanding and advanced moderation with large vision language models, spanning avatars, images, videos, audios, text, code / data models, and their composites. \n In close collaboration with product, policy, and Trust \u0026 Safety teams, you'll design large-scale systems to detect and mitigate abusive behavior before it harms the community. You'll own critical services at massive scale, balancing user freedom with platform civility to protect and empower our users. Your leadership will help ensure Roblox remains a safe, inclusive space for self-expression and shared experiences.\n You Will \n \n Own the vision, technical direction, and execution of machine learning solutions for the Multimodal Safety AI system, ensuring these systems effectively detect and prevent harmful content at scale.\n Lead and grow a high-performing team of ML engineers, fostering a culture of innovation, technical excellence, accountability, and inclusivity, while mentoring and developing talent.\n Break down ambitious long-term goals into an actionable, iterative roadmap – delivering continuous improvements in stages and driving tangible value at each step.\n Architect and guide the development of large-scale machine learning models with innovative architectures, ensuring they achieve high quality and are production-ready.\n Drive alignment on complex technical decisions across multiple teams (within and beyond the Safety org), demonstrating empathy and building consensus among diverse stakeholders.\n Collaborate cross-functionally with Product, Data Science, Policy, Design, and Operations partners to define and prioritize the machine learning roadmap for multimodal safety initiatives, ensuring alignment with broader Safety and Roblox objectives.\n Stay ahead of emerging trends in AI/ML and content moderation techniques, continuously innovating our safety approaches to anticipate new challenges. \n \n You Have \n \n 5+ years of experience building large-scale machine learning systems in production environments.\n Proven track record of designing, developing, and launching ML models from scratch into production.\n 2+ years of hands-on experience with vision language models or other foundation model technologies.\n Expertise in solving complex ML modeling, data, and infrastructure challenges – with a focus on maintaining high quality and velocity at scale.\n Ability to thrive in ambiguity: you excel at bringing clarity and direction to undefined or open-ended problem spaces.\n Demonstrated success collaborating across functions (e.g. Product, Design, Data, Research), working together to drive meaningful business and user impact.\n Strong product sense: able to establish clear success metrics and craft strategic roadmaps to achieve those goals.\n High emotional intelligence: adept at resolving conflicts, mentoring engineers, and nurturing the growth of your team members.\n Experience with modern microservice architectures and distributed systems programming paradigms (e.g. cloud services, scalable data pipelines).\n Hands-on to dive into code/architecture and guide technical discussions when needed, in addition to high-level planning. \n \n You Are \n \n Creative and strategic problem-solver: able to distill complex issues into simple, innovative solutions that drive impact.\n An owner: you take responsibility for projects and outcomes end-to-end, and instill the same accountability in your team.\n A lifelong learner: constantly seeking new knowledge and techniques to grow your expertise and expand your impact.\n Independent and self-directed: capable of charting a course with minimal guidance, and comfortable making decisions in uncertain situations.\n Highly collaborative: effective at working with cross-functional partners and teams, and skilled a","salary_min":295250,"salary_max":345040,"location":"San Mateo, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["data-pipeline","generative-ai","microservices","distributed-systems","machine-learning"],"apply_url":"https://careers.roblox.com/jobs/8047877?gh_jid=8047877","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-16T02:50:02Z","expires_at":"2026-08-15T14:18:31.254864Z","created_at":"2026-07-16T14:18:31.377819Z","updated_at":"2026-07-16T14:18:31.377819Z","company_name":"Roblox","company_slug":"roblox","company_logo_url":"https://www.google.com/s2/favicons?domain=roblox.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/acccc186-1fa0-414d-bb62-82bf62875fe7"},{"id":"9313b027-a169-43a5-b77c-bcd6097769df","company_id":"332b7698-676b-4a3e-8b02-81b1195c5af6","title":"Senior Software Engineer, Foundation Model API","slug":"senior-software-engineer-foundation-model-api-c724567b","description":"P-1428 \n At Databricks, we are passionate about enabling data and AI teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer-obsessed — we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started.\n As part of the AI team, you'll build the platforms and products that power everything from data apps, AI agents, model training, model serving, and Vector Search. You'll be joining a high-agency, high-visibility team operating at the frontier of AI infrastructure — with deep ties to research, product, and real-world enterprise use cases. Databricks Mosaic AI is one of our fastest-growing businesses, helping thousands of our customers democratize AI within their organizations. We're building the products and infrastructure that power the next generation of AI.\n We're hiring across multiple teams in our AI Engineering org, including the FMAPI (Foundation Model APIs) team — the unified serving layer for large language models across real-time and batch inference, powering model inference at enterprise scale. We are looking to hire high-agency L6 Engineers who bridge the gap between technical execution and product strategy.\n The impact you will have: \n \n Build LLM infrastructure powering large-scale inference workloads for customers through partner models (OpenAI, Anthropic, Gemini) and self-hosted models (Qwen, GPT-OSS, Llama)\n Shape the direction of the FMAPI product — from roadmap to execution — by leveraging deep customer empathy and direct engagement with enterprise users and model providers\n Improve reliability, latency, and efficiency of distributed AI workloads\n Collaborate with platform, infra, and ML teams to deliver seamless end-to-end experiences\n Shape how developers and data scientists build and interact with AI on Databricks\n \n What we look for: \n \n 8+ years of experience in backend or infrastructure engineering\n Experience with distributed systems, scalable APIs, or cloud-native infrastructure\n Strong product and ownership mindset, with a focus on shipping user-facing value\n Experience with real-time serving, ML infrastructure, or GPU orchestration\n Familiarity with service-oriented architecture, deployment pipelines, and system observability\n Strong programming skills in Scala, Go, or Python\n \n Bonus points for: \n \n Exposure to platforms like SageMaker, Vertex AI, or Azure ML\n Built products that support AI workflows\n  \n Pay Range Transparency \n Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles.  Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here . \n  \n Local Pay Range\n $160,000 — $225,000 USD \n About Databricks \n Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on  Twitter ,  LinkedIn   and   Facebook . Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here . \n Our Commitment to Diversity and Inclusion \n At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, soc","salary_min":160000,"salary_max":225000,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["distributed-systems","llm","generative-ai","agents","cloud","mlops","data-pipeline"],"apply_url":"https://databricks.com/company/careers/open-positions/job?gh_jid=8635900002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-15T21:49:06Z","expires_at":"2026-08-15T14:02:30.870498Z","created_at":"2026-07-16T14:02:30.99446Z","updated_at":"2026-07-16T14:02:30.99446Z","company_name":"Databricks","company_slug":"databricks","company_logo_url":"https://www.google.com/s2/favicons?domain=databricks.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/9313b027-a169-43a5-b77c-bcd6097769df"},{"id":"e252b0d3-026f-4e7a-98f1-906d9dc18f76","company_id":"332b7698-676b-4a3e-8b02-81b1195c5af6","title":"Senior Software Engineer, AI Native Web Platform","slug":"senior-software-engineer-ai-native-web-platform-0573785b","description":"P-1580\n About Us:\n The Web Engineering team at Databricks builds and owns the public-facing web experiences that represent Databricks to the world, across databricks.com, the blog, landing pages, hubs, microsites, and event properties. We are rebuilding the platform from the ground up, AI native from the start, and pioneering an agentic SDLC as our operating model.\n The Role:\n As Senior Software Engineer, AI Native Web Platform on the Web Engineering team, you will build and scale the platform layer that Web Engineering builds on: framework, infrastructure, CI/CD, and deployment pipelines. You will work under the direction of the Staff Software Engineer and contribute to a unified, agentic-ready foundation that shifts platform maintenance from per-surface effort to a centralized, scalable system.\n The impact you’ll have :\n \n Build and scale platform infrastructure including CI/CD pipelines, deployment automation, secrets management, and edge delivery configurations that power all of databricks.com \n Own accessibility testing in CI, bringing automated a11y validation into the deployment pipeline so accessibility is enforced at every release rather than caught after the fact \n Implement consent management infrastructure at the platform layer, replacing fragmented per-surface implementations with a centralized, policy-driven system that enforces compliance automatically across all web properties \n Contribute to tech stack unification: consolidating a fragmented set of frameworks and deployment models onto a shared design system and unified deployment foundation \n Operate in an AI native SDLC where agents assist across code generation, testing, and deployment, building faster and more reliably alongside them\n \n What we look for:\n \n 8+ years of software engineering experience with a track record of shipping and operating production web infrastructure \n Strong expertise across web platform infrastructure including CI/CD, deployment pipelines, build systems, and edge delivery \n Experience implementing or operating consent management systems at the platform layer \n Familiarity with accessibility standards and experience integrating automated a11y testing into CI pipelines is a strong plus\n Ability to own a platform infrastructure domain end to end and drive it to production under Staff direction \n Experience with tech stack consolidation or framework migration on live production systems is a strong plus\n  \n Pay Range Transparency \n Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles.  Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here . \n  \n Zone 1 Pay Range\n $159,900 — $219,900 USD \n About Databricks \n Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on  Twitter ,  LinkedIn   and   Facebook . Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here . \n Our Commitment to Diversity and Inclusion \n At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.\n Compliance \n If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.","salary_min":159900,"salary_max":219900,"location":"Mountain View, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["data-pipeline","code-generation","agents","platform"],"apply_url":"https://databricks.com/company/careers/open-positions/job?gh_jid=8635216002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-15T20:33:01Z","expires_at":"2026-08-15T14:02:30.530787Z","created_at":"2026-07-16T14:02:30.653714Z","updated_at":"2026-07-16T14:02:30.653714Z","company_name":"Databricks","company_slug":"databricks","company_logo_url":"https://www.google.com/s2/favicons?domain=databricks.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/e252b0d3-026f-4e7a-98f1-906d9dc18f76"},{"id":"f12c12c4-a7d1-45a9-aeb2-8c7854cf805a","company_id":"332b7698-676b-4a3e-8b02-81b1195c5af6","title":"Staff Software Engineer, AI Native Web Platform","slug":"staff-software-engineer-ai-native-web-platform-33e5b1da","description":"Staff Software Engineer, AI-Native Web Platform \n GAQ327R228 \n About Us: \n The Web Platform team at Databricks builds and owns the public-facing web experiences that represent Databricks to the world. We are rebuilding the platform from the ground up, AI-native from the start, and pioneering an agentic SDLC as our operating model. \n The Role: \n As Staff Software Engineer on the Web Platform team, reporting to the Director of Engineering, you will own the platform layer that the rest of the team builds on: web framework, design system, CMS, infrastructure, CI/CD pipelines, AI-enabled translation, and SDLC agents.  \n This is a rare opportunity to design a web platform for an AI-native world from the ground up. The north star architecture is being defined now and you will be a primary author of it. You will partner with technical leaders across web and marketing engineering, and set the standard for what AI-native platform engineering looks like in practice. \n The impact you’ll have : \n \n Define the technical roadmap for the web platform: component systems, rendering architecture, CMS, CI/CD pipelines, and developer tooling, built AI-native from the start.  \n Influence technical leaders across the organization on shared architectural decisions and contribute to the broader north star for AI-native engineering at Databricks.  \n Pioneer an AI-native SDLC by applying agentic unlocks across code generation, testing, review, deployment, and production monitoring.  \n Define the evaluation frameworks, guardrails, and feedback loops that make agentic workflows reliable and production-grade.  \n Mentor and grow engineers on the team, setting the standard for what AI-native thinking and execution looks like in practice. \n \n What we look for: \n \n 12+ years of software engineering experience, with a strong track record of technical leadership and impact. \n 3+ years of engineering leadership experience, serving as the technical owner for the software systems owned by your team. \n Proven track record as a technical leader of a web platform, with direct ownership across design systems, rendering frameworks, and understanding of edge delivery, CI/CD and infrastructure \n Deep hands-on expertise across the full web stack like React, TypeScript, Node.js. \n Demonstrated ability to make and execute multi-layer architectural decisions on a live production platform \n Experience sequencing and executing frontend framework migrations without disrupting production  \n A clear point of view on AI-native software development and a track record of building toward it \n Familiarity with agentic systems or LLM-powered tooling is a strong plus. \n Strong ability to influence technical leaders and drive alignment across engineering and business stakeholders \n History of driving technical transformation with rigor and execution discipline: stack consolidation, or platform-level standards adoption at scale \n  \n Pay Range Transparency \n Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles.  Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here . \n  \n Zone 1 Pay Range\n $198,200 — $272,600 USD \n About Databricks \n Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on  Twitter ,  LinkedIn   and   Facebook . Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here . \n Our Commitment to Diversity and Inclusion \n At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physica","salary_min":198200,"salary_max":272600,"location":"Mountain View, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["llm","data-pipeline","computer-graphics","agents","code-generation","platform"],"apply_url":"https://databricks.com/company/careers/open-positions/job?gh_jid=8635188002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-15T20:30:46Z","expires_at":"2026-08-15T14:02:34.842853Z","created_at":"2026-07-16T14:02:35.024216Z","updated_at":"2026-07-16T14:02:35.024216Z","company_name":"Databricks","company_slug":"databricks","company_logo_url":"https://www.google.com/s2/favicons?domain=databricks.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/f12c12c4-a7d1-45a9-aeb2-8c7854cf805a"},{"id":"b2503a2d-d800-43bc-9f84-11af04a6a4b4","company_id":"77beb456-fc80-40a4-b773-f0b17d1ece4c","title":"Generative AI - Graphics Engineer","slug":"generative-ai-graphics-engineer-429a27ce","description":"WHO YOU ARE\n\nWe are looking for skilled graphics engineer who have a deep command of modern C++ and GPU programming, a strong mathematical foundation, and an expert understanding of computer graphics—whether rendering, geometry processing, simulation, or advanced real-time techniques. You collaborate naturally with artists, researchers, and engineers, explaining complex ideas with clarity and learning from diverse perspectives. You’re not afraid of new ideas or unfamiliar pipelines. Most importantly, you’re excited to build the next generation of 3D creation technology—graphics systems that will empower millions of creators worldwide.\n\n\nWHO WE ARE\n\nAt Meshy, we believe 3D creation should be boundless and accessible. Our mission statement is simple: unleash creativity. We built a full pipeline for 3D content ranging from text / image to 3D, texturing, texture editing, animation rigging, etc. We also built a vibrant community for our creators, where people can share their work, take inspiration from others, and even use it as an asset marketplace for their games and prototypes. We are the market leader in 3D generative AI, recognized as the No.1 in popularity among 3D AI tools (according to 2024 A16Z Games survey), and we generate real value and is used by enterprises (including Meta, Square Enix, Deepmind, etc.) and millions of end users. Meshy is used in game and film production, in 3D printing, in industrial product design, in enablement of novel product features such as user-generated content, and even in training and simulation for robotics and physical AI.\n\n\nYOUR NEXT CHALLENGE\n\nAs a core member of Meshy’s algorithm team, you will design and build the next generation of high-performance graphics systems that power our 3D generative AI training and products. You will collaborate closely with graphics experts, generative AI researchers, and infrastructure engineers to enable new creative capabilities and push the boundaries of what AI-empowered 3D pipelines can achieve.\n\n \n\nIn this role, you will:\n\n - Build and optimize high-performance graphics components—rendering kernels, geometry processing operators, and supporting systems.\n\n - Develop robust production-quality pipelines that integrate with data pipelines, generative models and artist-facing applications.\n\n - Work across GPU clusters, cloud environments, and local DCC tools to ensure seamless interoperability and scalability.\n\n - Collaborate closely with artists, product teams, and ML researchers to translate creative requirements into technical implementations.\n\n - Contribute to internal tooling, demos, documentation, open-source initiatives, or technical reports that elevate Meshy’s graphics capabilities.\n\n\nWHAT WE'RE LOOKING FOR\n\n - Expert-level C++ and GPU programming skills, with a strong ability to write high-performance, memory-efficient code.\n\n - Solid mathematical foundation with deep understanding of computer graphics—either rendering, geometry processing, or both.\n\n - Hands-on experience building production-grade graphics systems, such as rendering engines, geometry pipelines, asset tools, or similar large-scale systems.\n\n - Strong engineering discipline—clean code, reproducible results, rigorous profiling, and sustainable system design.\n\n - Working knowledge of major DCC tools (Houdini, Blender, Maya), including experience developing scripts, plug-ins, or custom tools within these environments is a plus.\n\n - Experience in AAA game development, VFX pipelines, or other high-end 3D production environments is a plus.\n\n - Demonstrated contributions to open-source graphics projects or publications in top-tier CG venues (SIGGRAPH, etc.) are pluses.\n\n\nA LITTLE MORE ABOUT MESHY.AI\n\nTrusted by Meta, Square Enix, Deepmind and more, Meshy is redefining 3D creation with generative AI. We empower artists, designers, engineers, hobbyists, and makers to bring immersive worlds, characters, and experiences to reality in minutes instead of months.\n\n \n\nIn addition to our core mission of unleashing creativity, we build a culture that we enjoy and are proud of. Here are some highlights:\n\n - We value intelligence and the pursuit of knowledge. We are a global team of generative-AI pioneers, computer-graphics veterans, and product builders who believe human expression and enjoyment is the ultimate frontier of computing.\n\n - We care deeply about our work, our users, and each other. Empathy and passion drive us forward. We have a culture of directness and truthfulness, therefore we value constructive criticism. Being direct and truthful is the most sincere form of trust and care.\n\n - We trust our instincts and are not afraid to take bold risks. Meshy was born from a few-hour prototype, a bold pivot for a team that had very little experience in AI. Innovation requires courage.\n\n - We have a keen eye for quality and aesthetics. Our products are not just functional but also beautiful. The same aesthetics permeate through our culture, our code and ","salary_min":175000,"salary_max":300000,"location":"San Francisco, CA","workplace":"remote","remote_scope":"unknown","job_type":"full-time","experience_level":"senior","tags":["gpu","generative-ai","data-pipeline","robotics","computer-graphics","research"],"apply_url":"https://jobs.ashbyhq.com/meshy/e08ff336-379d-4cde-8df0-c5ab335517b3/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-15T20:04:34.461Z","expires_at":"2026-08-15T14:10:57.040052Z","created_at":"2026-07-16T14:10:57.180092Z","updated_at":"2026-07-16T14:10:57.180092Z","company_name":"Meshy","company_slug":"meshy","company_logo_url":"https://www.google.com/s2/favicons?domain=meshy.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/b2503a2d-d800-43bc-9f84-11af04a6a4b4"},{"id":"c86d2f91-914b-4899-b3e1-e61be0732f6a","company_id":"77beb456-fc80-40a4-b773-f0b17d1ece4c","title":"Generative AI - ML System Engineering","slug":"generative-ai-ml-system-engineering-b7b36ecf","description":"WHO YOU ARE\n\nWe are looking for Machine Learning Systems Engineers who can help us build the world's largest end-to-end 3D native machine learning systems. You will help us build our end to end ML framework dedicated for 3D, from pretraining, to finetuning, inferencing, etc. We expect a combination of strong hands on engineering skills, eagerness to learn new things, and thrives in a fast-paced, high-ownership environment.\n\n\nWHO WE ARE\n\nAt Meshy, we believe 3D creation should be boundless and accessible. Our mission statement is simple: unleash creativity. We built a full pipeline for 3D content ranging from text / image to 3D, texturing, texture editing, animation rigging, etc. We also built a vibrant community for our creators, where people can share their work, take inspiration from others, and even use it as an asset marketplace for their games and prototypes. We are the market leader in 3D generative AI, recognized as the No.1 in popularity among 3D AI tools (according to 2024 A16Z Games survey), and we generate real value and is used by enterprises (including Meta, Square Enix, Deepmind, etc.) and millions of end users. Meshy is used in game and film production, in 3D printing, in industrial product design, in enablement of novel product features such as user-generated content, and even in training and simulation for robotics and physical AI.\n\n\nYOUR NEXT CHALLENGE\n\n3D is the brave new frontier of Gen AI. Our work here involves a lot of unique new challenges in both training and inference. Your next challenge at Meshy would involve the full stack of AI, from debugging and monitoring the hardware platform, building training framework, scaling high-throughput 3D data pipelines for our foundational training, co-designing novel model architectures with researchers, to the novel challenge of efficient inference engines for diffusion models and more. Here are some examples for each side of the challenge:\n\n \n\nOn the training side\n\n - Work closely with researchers to co-design the next frontier of 3D \u0026 Spatial AI.\n\n - Build and debug on top of modern PyTorch, for maximum parallelism and efficiency, and build clean and intuitive training infrastructure for our in-house foundational models.\n\n - Identifying bottlenecks and optimizing for high throughput \u0026 efficient distributed model training across hundreds to thousands of GPUs.\n\n - Implementing and maintaining 3D specific custom operators in Triton or CUDA.\n\n - Implementing and maintaining novel data-loading framework and libraries.\n\nOn the inference side\n\n - Building efficient inference endpoints with complex multi-stage model pipelines.\n\n - Optimizing models through compilation, fusion, quantization, etc.\n\n\nWHAT WE'RE LOOKING FOR\n\n - Experience in machine learning or high performance graphics.\n\n - Solid practical understanding of at least one machine learning framework (e.g. PyTorch, JAX).\n\n - Strong ability to write beautiful and maintainable code in Python and/or C++.\n\n - Ability to learn fast and dive into new concepts or complex codebases.\n\n - Performance and efficiency oriented mindset, with a strong interest in the tiniest detail.\n\n - Strong communication skills for working in a globally distributed team.\n\n\nNICE TO HAVE\n\n - A strong passion to navigate through the PyTorch internals, with hands-on experience in areas like torch.compile , fully_shard (FSDP2) APIs.\n\n - Experience with building Triton kernels.\n\n - Experiences with large-scale distributed training, familiarity with modern parallelization techniques: DP, TP, CP, PP, zero redundancy optimizers, etc.\n\n - Experience with diffusion models in 3D or video.\n\n - Experience with low precision bf16 or fp8 training.\n\n\nA LITTLE MORE ABOUT MESHY.AI\n\nTrusted by Meta, Square Enix, Deepmind and more, Meshy is redefining 3D creation with generative AI. We empower artists, designers, engineers, hobbyists, and makers to bring immersive worlds, characters, and experiences to reality in minutes instead of months.\n\n \n\nIn addition to our core mission of unleashing creativity, we build a culture that we enjoy and are proud of. Here are some highlights:\n\n - We value intelligence and the pursuit of knowledge. We are a global team of generative-AI pioneers, computer-graphics veterans, and product builders who believe human expression and enjoyment is the ultimate frontier of computing.\n\n - We care deeply about our work, our users, and each other. Empathy and passion drive us forward. We have a culture of directness and truthfulness, therefore we value constructive criticism. Being direct and truthful is the most sincere form of trust and care.\n\n - We trust our instincts and are not afraid to take bold risks. Meshy was born from a few-hour prototype, a bold pivot for a team that had very little experience in AI. Innovation requires courage.\n\n - We have a keen eye for quality and aesthetics. Our products are not just functional but also beautiful. The same aesthetics permeate through our culture, our code and are the ","salary_min":175000,"salary_max":300000,"location":"San Francisco, CA","workplace":"remote","remote_scope":"unknown","job_type":"full-time","experience_level":"senior","tags":["fine-tuning","pytorch","distributed-systems","pre-training","generative-ai","gpu","robotics","data-pipeline"],"apply_url":"https://jobs.ashbyhq.com/meshy/3f94dcd6-9d31-47e7-a6b1-66e49a777056/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-15T19:52:38.747Z","expires_at":"2026-08-15T14:10:55.956272Z","created_at":"2026-07-16T14:10:56.084849Z","updated_at":"2026-07-16T14:10:56.084849Z","company_name":"Meshy","company_slug":"meshy","company_logo_url":"https://www.google.com/s2/favicons?domain=meshy.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/c86d2f91-914b-4899-b3e1-e61be0732f6a"},{"id":"6db6f99f-a30e-4524-a8e4-b34154992b4d","company_id":"77beb456-fc80-40a4-b773-f0b17d1ece4c","title":"Generative AI - 3D Foundation Model","slug":"generative-ai-3d-foundation-model-cb2667cc","description":"WHO YOU ARE\n\nYou are a talented, hands-on researcher who thrives in a fast-paced environment, is self-directed, a team player, and knows how to get things done efficiently. You have deep understanding of the transformer architecture, have strong python and tensor programming skills, have a vision for AI beyond linear sequences, and you believe in \"the scaling law\". You can translate high-level goals into concrete research and implementation steps, set an approach, and follow through. When it's time to explain your ideas, you bring clarity to complex technical issues. You are not afraid of confronting new ideas, and you are eager to share your knowledge with the team. You use these skills to create real-world benefits for our researchers, engineers, and millions of users, and you are excited to help advance our effort to push the state of the art of AI that understands and generates 3D worlds.\n\n\nWHO WE ARE\n\nAt Meshy, we believe 3D creation should be boundless and accessible. Our mission statement is simple: unleash creativity. We built a full pipeline for 3D content ranging from text / image to 3D, texturing, texture editing, animation rigging, etc. We also built a vibrant community for our creators, where people can share their work, take inspiration from others, and even use it as an asset marketplace for their games and prototypes. We are the market leader in 3D generative AI, recognized as the No.1 in popularity among 3D AI tools (according to 2024 A16Z Games survey), and we generate real value and is used by enterprises (including Meta, Square Enix, Deepmind, etc.) and millions of end users. Meshy is used in game and film production, in 3D printing, in industrial product design, in enablement of novel product features such as user-generated content, and even in training and simulation for robotics and physical AI.\n\n\nYOUR NEXT CHALLENGE\n\nAs a core member of the team of research scientists and machine learning engineers at Meshy, you will drive the development of our core 3D-native generative foundational model. In this role, you will join our foundational research to advance 3D AI, apply learnings from other fields of ML, and pushing the state of the art. You will also work towards long-term ambitious research goals, while identifying intermediate milestones.\n\n \n\nThe essential functions include, but are not limited to the following:\n\n - Design, train, and refine large-scale 3D generative models from covering pre-training, post-training, and emerging paradigms in diffusion, flow matching, and multi-modal learning.\n\n - Bridge the gap between cutting-edge research and product, deploy models in real products used by millions of creators, using human feedback and creative evaluation.\n\n - Create novel model architectures to make 3D generation faster, higher-quality, and more controllable.\n\n - Collaborate with infrastructure and systems teams to build scalable training, and data pipelines across GPU clusters and cloud environments.\n\n - Bring engineering discipline into an fast-paced research environment: elegant code, reproducible experiments, and building software as a team.\n\n - Share insights and breakthroughs through internal demos, open-source contributions, or technical reports that advance the field of 3D generative AI.\n\n\nWHAT WE'RE LOOKING FOR\n\n - Strong engineering skills in Python and deep learning frameworks (preferably PyTorch); comfortable moving between research prototypes and production systems.\n\n - Familiar with Transformers and modern generative AI models (Diffusion / flow matching, VAE, etc.).\n\n - Curiosity and passion for multi-modal AI, and have an intuitive understanding of how models perceive, represent, and generate 3D worlds.\n\n - Familiar with high performance training on large scale infrastructure (e.g., SLURM, Ray, k8s) is a plus.\n\n - Contributions to popular open-source machine learning projects or publications in top-tier CV / ML conferences is a plus.\n\n\nA LITTLE MORE ABOUT MESHY.AI\n\nTrusted by Meta, Square Enix, Deepmind and more, Meshy is redefining 3D creation with generative AI. We empower artists, designers, engineers, hobbyists, and makers to bring immersive worlds, characters, and experiences to reality in minutes instead of months.\n\n \n\nIn addition to our core mission of unleashing creativity, we build a culture that we enjoy and are proud of. Here are some highlights:\n\n - We value intelligence and the pursuit of knowledge. We are a global team of generative-AI pioneers, computer-graphics veterans, and product builders who believe human expression and enjoyment is the ultimate frontier of computing.\n\n - We care deeply about our work, our users, and each other. Empathy and passion drive us forward. We have a culture of directness and truthfulness, therefore we value constructive criticism. Being direct and truthful is the most sincere form of trust and care.\n\n - We trust our instincts and are not afraid to take bold risks. Meshy was born from a few-hour prototype, a bold pivot","salary_min":175000,"salary_max":300000,"location":"San Francisco, CA","workplace":"remote","remote_scope":"unknown","job_type":"full-time","experience_level":"senior","tags":["generative-ai","gpu","robotics","deep-learning","data-pipeline","pre-training","pytorch","research"],"apply_url":"https://jobs.ashbyhq.com/meshy/f52aa172-0212-4db8-a93d-406b910b9fea/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-15T19:18:36.925Z","expires_at":"2026-08-15T14:10:56.873764Z","created_at":"2026-07-16T14:10:56.993732Z","updated_at":"2026-07-16T14:10:56.993732Z","company_name":"Meshy","company_slug":"meshy","company_logo_url":"https://www.google.com/s2/favicons?domain=meshy.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/6db6f99f-a30e-4524-a8e4-b34154992b4d"},{"id":"9cf703e4-28cb-47a7-9151-d26f9745f43d","company_id":"74257563-5513-4a8d-a0f7-01f00c59aed6","title":"Senior Machine Learning Engineer, Relevance and Personalization (Query Intelligence)","slug":"senior-machine-learning-engineer-relevance-and-personalization-query-intelligence-b6fdeb9a","description":"Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way. \n The Community You Will Join: \n The Relevance and Personalization team at Airbnb is responsible for search and recommendation across the entire Airbnb digital platform. In this role you'll focus on query intelligence, the front door of search working on critical, impactful projects that turn what a guest types, taps, or says into a precise understanding of their intent, spanning autocomplete and smart compose, query tagging, query expansion, and intent modeling across Stays, Experiences, and Services.\n The Difference You Will Make: \n Query understanding is where every search begins, and it directly shapes retrieval, ranking, and ultimately the perfect match between guests and hosts. We build cutting-edge AI technologies across the end-to-end search ranking product stack w.r.t. data pipelines, feature and model innovations, serving and experimentation efficiency, leveraging rich signals from various types of data (structured, sequential, image, text, etc) and increasingly large language models at Airbnb. You'll build the models that parse free-form and natural-language multimodal queries, extract entities and location context, classify intent, and anticipate what guests want before they finish typing. We collaborate closely with teams across Airbnb to develop the ranking solutions and support a healthy marketplace for hosts and guests to further Airbnb's mission of creating a world where people can Belong Anywhere. Some past publications from the team can be found here: https://sites.google.com/view/airbnb-relevance-publications/home \n A Typical Day:  \n \n Work with large scale structured and unstructured data, build and continuously improve cutting edge Machine Learning models for Airbnb product, business and operational use cases, with a focus on query understanding.\n Develop query understanding capabilities — autocomplete and smart compose, query tagging (sequence tagging / NER), query expansion, and query/user intent modeling — and natural-language (\"search in your own words\") search experiences powered by modern NLP and LLMs.\n Work collaboratively with cross-functional partners including software engineers, product managers, operations and data scientists, identify opportunities for business impact, understand, refine, and prioritize requirements for machine learning models, drive engineering decisions, and quantify impact.\n Hands-on develop, productionize, and operate Machine Learning models and pipelines at scale, including both batch and real-time use cases.\n Leverage third-party and in-house Machine Learning tools \u0026 infrastructure to develop reusable, highly differentiating and high-performing Machine Learning systems, enable fast model development, low-latency serving and ease of model quality upkeep.\n Example projects include: smart compose and language generation for search, LLM-based sequence taggers, LLM-driven query/location expansion, intent classification, and user-intent sequence modeling.\n \n Your Expertise: \n \n 5+ years of industry experience in applied Machine Learning, inclusive MS or PhD in relevant fields.\n Strong programming (Scala / Python / Java / C++ or equivalent) and data engineering skills.\n Deep understanding of Machine Learning best practices (eg. training/serving skew minimization, A/B test, feature engineering, feature/model selection), algorithms (eg. neural networks/deep learning, optimization) and domains (eg. natural language processing, personalization, search and recommendation, marketplace optimization).\n Experience with 3 or more of these technologies: Tensorflow, PyTorch, Kubernetes, Spark, Airflow (or equivalent), Kafka (or equivalent), data warehouse (eg. Hive).\n Industry experience building end-to-end Machine Learning models.\n Experience applying large language models and modern NLP — e.g., sequence tagging/NER, text generation, intent classification, or embedding/representation learning.\n Familiarity with building natural-language, AI-native and agentic search experiences is a plus.\n Exposure to architectural patterns of large, high-scale software applications (e.g., well-designed APIs, high volume data pipelines, efficient algorithms, models).\n \n Your Location: \n This position is US - Remote Eligible. The role may include occasional work at an Airbnb office or attendance at offsites, as agreed to with your manager. While the position is Remote Eligible, you must live in a state where Airbnb, Inc. has a registered entity. Click here for the up-to-date list of excluded states. This list is continuously evolving, so please check back with us if the state you live in is on the exclusion list. If your po","salary_min":200000,"salary_max":235000,"location":"United States","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["tensorflow","agents","search","data-pipeline","deep-learning","generative-ai","llm","pytorch"],"apply_url":"https://careers.airbnb.com/positions/8065789?gh_jid=8065789","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-14T23:54:51Z","expires_at":"2026-08-15T14:10:04.208902Z","created_at":"2026-07-15T14:11:23.002744Z","updated_at":"2026-07-16T14:10:04.325662Z","company_name":"Airbnb","company_slug":"airbnb","company_logo_url":"https://www.google.com/s2/favicons?domain=airbnb.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/9cf703e4-28cb-47a7-9151-d26f9745f43d"},{"id":"96c4b57f-c214-4de0-829c-cda4957c7a17","company_id":"a0000000-0000-0000-0000-000000000003","title":"Senior Software Engineer, Agent Oversight","slug":"senior-software-engineer-agent-oversight-a8682235","description":"About Scale\n Scale’s mission is to develop reliable AI systems for the world’s most important decisions. As the leading AI data foundry, we provide the high-quality data and full-stack technologies that power the world’s most advanced models — fueling breakthroughs in generative AI, defense, and autonomous vehicles. We partner with leading enterprises and governments to bring AI into production that performs when it matters most, combining rigorous evaluation with full-stack deployment so our customers can build AI they can trust.\n About the Team\n Applied Intelligence Systems team is part of the Scale Generative AI Platform (SGP), focused on pushing the frontier of what agentic applications can do across diverse enterprise and government use cases. We build the infrastructure and tooling that power Agentic AI in production, paired with applied ML research, design, and evaluation to ensure these systems perform reliably at the scale our customers demand. We’re growing fast, with increasing traction across both commercial and public sector customers, and we’re just getting started — this team will define what dependable, production-grade agentic AI looks like.\n About the Role\n As a Software Engineer on Agent Oversight, you will build the platform infrastructure that lets our production agents be observed, evaluated, and improved at scale. This includes building observability tooling, evaluation harnesses, and the pipelines that connect them to improvement loops. Whether building foundational infrastructure or partnering closely with ML engineers on production workflows, you will own your systems end-to-end while maintaining rigorous technical standards.\n You will:\n \n Design and build core platform capabilities for deploying, monitoring, and evaluating agentic applications in production\n Build reliable APIs and data pipelines that capture agent telemetry, evaluation signals, and performance metrics at scale\n Work alongside ML engineers where platform work intersects with evaluation or improvement systems — bringing enough ML fluency to reason about model behavior, evaluation quality, and improvement loops while owning the software systems that make those workflows reliable\n Own the reliability, scalability, and observability of platform components serving multiple concurrent enterprise and government customers\n Work cross-functionally with product, forward deployed engineering, and customers to translate real-world deployment requirements into platform features\n Build features end-to-end: system design, implementation, debugging, and testing\n Participate in high-velocity experimentation to validate platform capabilities against real customer usage\n \n Requirements:\n \n 4+ years of professional software engineering experience, with strong fundamentals in backend/distributed systems, APIs, and data pipeline design\n Hands-on experience building production software for ML/LLM-powered products or platforms, such as evaluation systems, observability/monitoring, experimentation infrastructure, agent runtimes, model-serving-adjacent services, or telemetry/data pipelines\n Working knowledge of how LLM or ML systems behave in production: evaluation signals, failure modes, prompt/tool-calling workflows, experiment results, data quality issues, and the tradeoffs between offline evals and live customer behavior\n Experience partnering closely with ML engineers or applied researchers to turn prototypes, eval loops, or model-improvement workflows into reliable platform capabilities, without needing to own model training, modeling strategy, or research direction\n Experience building infrastructure or platforms that other engineering teams build on top of (internal platform, developer tools, or similar)\n Track record of taking ownership of features or components end-to-end — from design through production — within a larger platform or system\n Comfortable operating in an ambiguous, fast-changing domain where tooling and best practices are still being defined\n Strong problem-solving skills and the ability to work independently or as part of a tight-knit, cross-functional team\n Excited to work directly with ML engineers and customer-facing teams, including challenging assumptions in designs and metrics when platform behavior, model behavior, and customer needs intersect\n Gives direct, substantive feedback on designs and code, and takes it the same way — and mentors others as they grow\n \n Nice to have:\n \n Deep experience building or maintaining observability, monitoring, or evaluation systems for ML/LLM-powered products in production\n Familiarity with agent architectures — tool use, planning, multi-agent orchestration\n Exposure to MLOps, feature stores, model serving, or experiment infrastructure\n Experience working in regulated or enterprise contexts\n Experience reviewing others’ technical designs or mentoring engineers at a senior/staff level\n Compensation packages at Scale for eligible roles include base s","salary_min":216000,"salary_max":270000,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["mlops","autonomous-vehicles","llm","data-pipeline","distributed-systems","agents","generative-ai"],"apply_url":"https://job-boards.greenhouse.io/scaleai/jobs/4714509005","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-14T20:12:46Z","expires_at":"2026-08-15T14:01:43.763646Z","created_at":"2026-07-15T14:01:47.543291Z","updated_at":"2026-07-16T14:01:43.880972Z","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/96c4b57f-c214-4de0-829c-cda4957c7a17"},{"id":"53523380-38ba-4300-ab1a-a7402a41ff8f","company_id":"a0000000-0000-0000-0000-000000000001","title":"Staff+ Software Engineer, Capacity Engineering","slug":"staff-software-engineer-capacity-engineering-751b8b8f","description":"About Anthropic \n Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.\n About the Role \n Anthropic manages one of the largest and fastest-growing infrastructure fleets in the industry — spanning multiple accelerator families, cpu families and clouds. The Capacity Engineering team is responsible for making sure all our infrastructure resources are accounted for, well-utilized, and efficiently allocated. We own the data, tooling, and operational systems that let Anthropic plan, measure, and maximize utilization across first-party and third-party compute.\n As an engineer on Capacity Engineering, you will build the production systems that power this work: data pipelines that ingest and normalize telemetry from heterogeneous cloud environments, observability tooling that gives the org real-time visibility into fleet health, and performance instrumentation that measures how efficiently every major workload uses the hardware it’s running on. You will be expected to write production-quality code every day, operate alongside Kubernetes-native infrastructure at meaningful scale, and directly influence decisions around one of Anthropic’s largest areas of spend.\n You’ll collaborate closely with research engineering, infrastructure, inference, and finance teams. The work requires someone who can move between data engineering, systems engineering, and observability with comfort — and who thrives in a high-autonomy, high-ambiguity environment.\n This is a pipeline role feeding four areas. Depending on your background and business priority, you’ll focus primarily in one, but the boundaries are fluid and the problems overlap: \n \n Data platform Pipelines that ingest occupancy and utilization telemetry from Kubernetes clusters, normalize billing and usage across cloud providers, and serve the BigQuery tables the rest of the org queries against. Correctness, completeness, and latency are the job, not a footnote. Consumers range from research engineers to finance to leadership, so it's product work as much as engineering: defining schema contracts, making data discoverable, and figuring out what people actually need.\n Planning Knowing what the fleet has, where it's going, and what's in the way. Making the state of the fleet legible and actionable in real time: cluster health tooling, capacity planning platforms, alerting on occupancy drops and allocation problems, and systemic fixes to scheduling and fragmentation. Kubernetes operations on one side, cross-team coordination on the other.\n Efficiency Measuring and improving how effectively every major workload uses the hardware it runs on. Instrumenting utilization across training, inference, and eval systems, building benchmarking infrastructure, establishing per-config baselines, and working directly with system-owning teams to close the gaps. The metric has to be good enough that the team on the hook for it agrees with the number.\n Attribution and forecasting Connecting what the fleet costs to what the business is doing with it. Reconciling CSP billing exports against vendor telemetry and internal systems with mismatched schemas, attributing spend to the workloads and teams that generate it, and turning inference demand signals and research roadmaps into a defensible compute plan. Efficiency metrics have to survive contact with finance: stripped of pure demand and unit-price effects, reproducible month over month, and legible to a CFO.\n \n Key responsibilities \n \n Build the planning and allocation stack — the tools leadership uses to allocate capacity, teams use to plan against their allocations, and the scheduler enforces. Cross-region and cross-provider placement, guardrails, queueing, occupancy KPIs.\n Drive the efficiency programs: stranding and rightsizing, unused capacity recovery, and job-level utilization across training, inference, and eval. Establish per-config baselines and work with system-owning teams to close the gaps. At this fleet size a single point of utilization is worth eight figures a month.\n Own attribution and forecasting — reconcile billing across ten-plus providers against telemetry and internal systems, attribute spend to the workloads that generate it, and turn demand signals and research roadmaps into a defensible compute plan and supply pipeline.\n Build the data platform underneath all of it: pipelines ingesting occupancy, utilization, and cost from a rapidly diversifying fleet into BigQuery, with real ownership of completeness, latency SLOs, and gap detection. Every new provider is a net-new integration.\n Operate Kubernetes-native systems at scale — collection agents, workload labeling, and the taint/reservation/scheduling behavior that determines what capacity is ac","salary_min":320000,"salary_max":485000,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["search","data-pipeline","payments","infrastructure"],"apply_url":"https://job-boards.greenhouse.io/anthropic/jobs/5310731008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-14T19:16:22Z","expires_at":"2026-08-15T14:00:39.165919Z","created_at":"2026-07-15T14:00:36.496615Z","updated_at":"2026-07-16T14:00:39.319483Z","company_name":"Anthropic","company_slug":"anthropic","company_logo_url":"https://www.google.com/s2/favicons?domain=anthropic.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/53523380-38ba-4300-ab1a-a7402a41ff8f"},{"id":"f115ce97-f6c4-4c2d-9602-6a9e48528e12","company_id":"b6db41bc-ba14-4906-b2f7-a3ce9289a346","title":"Software Engineer, AI Platform","slug":"software-engineer-ai-platform-305af12e","description":"WHO WE ARE\n\nNotion is the collaborative AI workspace where teams and agents think together https://www.youtube.com/watch?v=vkpYpWfEK5s. We're building one place where your knowledge, projects, meetings, and AI tools live side by side, so work is faster, clearer, and less fragmented. Millions of individuals, small teams, and large companies run their work on Notion.\n\n\n\nNotinos (our employees) are customer zero in bringing this future of work to life. We care about craft, building things that last, and the belief that great work is still fundamentally human. Our goal isn’t to ship the next feature. Each and every team of Notinos is working to set the standard for how humans work together in the AI era. From building a business’s system of record to making and managing AI agents to automating away the busy work, we care deeply about giving our customers more time for their life’s work.\n\n\n\n\nABOUT THE ROLE:\n\nMillions of people use Notion — and this number is increasing every day. That means millions of people trust us to deliver a fast, reliable, and secure experience, and we value this more than anything. We want to keep earning trust, while also continuing to amaze our users with the tools they can build in Notion.\n\nThe AI Platform team is responsible for building the shared foundations that let Notion ship AI products quickly and operate them safely at scale. You’ll join a team of talented engineers focused on making speed and quality compatible: reliability and availability through provider changes, quality and correctness systems like evals and release gates, observability that makes failures explainable, and shared primitives for model integrations, context management, long-running actions, and cost/performance tradeoffs. Notion’s AI platform is vital to helping product teams move faster with production-grade guardrails as models, providers, and AI capabilities rapidly evolve.\n\nThis role can be based in either San Francisco or New York City. We work from our offices on Mondays, Tuesdays and Thursdays (our Anchor Days) because we do our best thinking and building together in person. We’re looking for someone who’s excited to work alongside the team during those days.\n\n\n\n\nWHAT YOU'LL ACHIEVE:\n\n - You'll own and play a pivotal role in the prototyping, development and scaling of systems and core AI platform primitives.\n\n - You’ll partner closely with product teams to provide paved paths and production-ready guardrails that help new AI features ship faster with less duplicated work.\n\n - You’ll work across infrastructure, shared libraries, APIs, and product integration points to make AI platform capabilities easy to adopt and high-leverage across Notion.\n\n - You’ll operate critical AI systems in production, using observability and diagnostics to understand provider/model behavior, debug failures, improve latency and cost, and evolve systems with minimal user disruption.\n\n - You’ll help Notion safely adopt new models, providers, and AI capabilities through versioning, controlled rollouts, compatibility layers, and clear quality/reliability gates.\n\n\n\n\nSKILLS YOU'LL NEED TO BRING:\n\n - Passion for AI systems at scale: You’ve worked on LLM, ML platform, data, or infrastructure teams that own critical shared systems. You understand the challenges of scaling reliability, latency, cost, and quality as usage and model complexity grow. You care deeply about building platforms that are dependable, efficient, and easy for other engineers to use.\n\n - Adaptable and curious: You like going deep on how systems behave in practice, especially when models, providers, and product requirements are changing quickly. You’re eager to use AI tools to work smarter and are willing to move across backend, infrastructure, libraries, and product code when that’s what the problem requires.\n\n - Extreme ownership: You’re comfortable working across ambiguous problem spaces, aligning stakeholders around a clear path forward, and driving execution with accountability. You take ownership of platform outcomes including reliability, quality, adoption, and operational follow-through beyond team boundaries.\n\n - Thoughtful problem-solving: For you, problem-solving starts with a clear and accurate understanding of the context. You can decompose ambiguous system behavior, debug across layers, and work toward clean, pragmatic solutions by yourself or with teammates. You’re comfortable asking for help when you get stuck.\n\n - Pragmatic and business-oriented: You understand that AI platform work is full of tradeoffs across quality, latency, cost, reliability, and speed of execution. You prioritize based on product and business impact, balancing craft with urgency and operational simplicity.\n\n\n\n\nNICE TO HAVES:\n\n - 2-4 years of experience as a Software Engineer\n\n - Experience with applied AI product development (prompting, evals, model integrations, or quality measurement).\n\n - You've built out and scaled data processing pipeli","salary_min":180000,"salary_max":201000,"location":"San Francisco, CA","workplace":"remote","remote_scope":"unknown","job_type":"full-time","experience_level":"junior","tags":["llm","mlops","data-pipeline","agents","platform"],"apply_url":"https://jobs.ashbyhq.com/notion/a9d4a192-d31c-48d2-8156-e2a75d98eec1/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-14T14:23:31.706Z","expires_at":"2026-08-15T14:03:39.597424Z","created_at":"2026-07-15T14:04:39.064153Z","updated_at":"2026-07-16T14:03:39.731671Z","company_name":"Notion","company_slug":"notion","company_logo_url":"https://www.google.com/s2/favicons?domain=notion.so\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/f115ce97-f6c4-4c2d-9602-6a9e48528e12"},{"id":"394498a7-3e09-4b7d-9dc4-98c2d5cce6a3","company_id":"ccb23d77-c69e-462b-a941-02ce99527e78","title":"Software Engineer I (Data Eng infra)","slug":"software-engineer-i-data-eng-infra-ce880ce9","description":"Who we are \n Aurora’s mission is to deliver the benefits of self-driving technology safely, quickly, and broadly.\n The Aurora Driver  will create a new era in mobility and logistics, one that will bring a safer, more efficient, and more accessible future to everyone.\n  \n At Aurora, you will tackle massively complex problems alongside other passionate, intelligent individuals, growing as an expert while expanding your knowledge. For the latest news from Aurora, visit  aurora.tech  or follow us on  LinkedIn .\n  \n What we are looking for \n Aurora hires talented people with diverse backgrounds who are ready to help build a transportation ecosystem that will make our roads safer, get crucial goods where they need to go, and make mobility more efficient and accessible for all. \n We are seeking a talented and experienced Software Engineer to join our data engineering and infrastructure team. In this role, you will be working with our seasoned engineers and contribute to the design, development, and maintenance of our data platform, building the scalable and reliable systems that enable our organization to leverage data for insights and product innovation. You will work on the core data lake and data warehouse ecosystem infrastructure, data pipelines, and tools that process data at massive scale, ensuring it is accessible, high-quality, and secure.\n In this role, you will \n \n Design, build, and maintain robust and scalable data pipelines and ETL/ELT processes to ingest, transform, and load data from various sources into our data warehouse.\n Develop and manage data infrastructure components using AWS cloud services and infrastructure-as-code tools like Terraform.\n Collaborate with data scientists, analysts, autonomy engineering teams and product teams to understand their data needs and build solutions that meet their requirements.\n Optimize data processing systems for performance, reliability, and cost-efficiency.\n Implement monitoring, alerting, and logging for data pipelines and infrastructure to ensure operational stability.\n Champion best practices in data governance, data quality, and security.\n \n Required Qualifications \n \n Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience.\n 1+ years of recent professional experience in software engineering, with a focus on data-related projects.\n Proficiency in at least one programming language commonly used for data engineering (e.g., Python, Go or C++).\n Preliminary experience with big data processing frameworks like Apache Spark, Flink, Kinesis Data Stream, or similar technologies.\n Hands-on experience with cloud platforms (AWS, GCP, or Azure) and their data services (e.g., S3, Redshift, BigQuery, Glue).\n Strong knowledge of SQL and experience working with relational and NoSQL databases.\n Preliminary knowledge of data analytics infrastructure, including data transformation tools such as DBT and visualization frameworks and tools\n Experience with building and managing data pipelines using an orchestrator like Apache Airflow.\n Able to systematically approach open-ended questions to identify pragmatic data solutions that scale\n Able to work effectively in a highly cross-functional, fast-moving and high-stakes environment\n Proven ability to communicate technical, data-driven solutions to both technical and non-technical audiences across stakeholders\n \n Desirable Qualifications  \n \n Experience with data warehousing solutions like Snowflake or data lake architectures.\n Familiarity with modern data stack tools and practices.\n A passion for building elegant, scalable, and maintainable systems.\n Experience using Amazon Web Services (AWS) tools\n \n The base salary wage range for this position is $116K-$174K per year.  Aurora’s pay ranges are determined by role, level, and location. Within the range, the successful candidate’s starting base pay will be determined based on factors including job-related skills, experience, qualifications, relevant education or training, and market conditions. These ranges may be modified in the future. The successful candidate will also be eligible for an annual bonus, equity compensation, and benefits. \n  #LI-SP1 \n Working at Aurora At Aurora, we bring together extraordinarily talented and experienced people united by the strength of our values. We operate with integrity, set outrageous goals, and build a culture where we win together — all without any jerks.\n We believe in-person work increases collaboration, empathy and our ability to lead effectively. As a result, we operate in a hybrid work environment where Aurorans are in office at least 3 days per week.\n Our Careers page provides insight into what it is like to work at Aurora, and you can find all the latest updates in our Newsroom .\n Our commitment to safety \n At the core of everything we do is our commitment to safety. Building best-in-class self-driving technology will take time, and we believe that each employee at ","salary_min":116000,"salary_max":174000,"location":"Mountain View, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"junior","tags":["data-pipeline","autonomous-vehicles","cloud","data-science","infrastructure"],"apply_url":"https://aurora.tech/jobs/8628066002?gh_jid=8628066002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-13T13:24:28Z","expires_at":"2026-08-15T14:05:24.523638Z","created_at":"2026-07-15T14:06:40.845277Z","updated_at":"2026-07-16T14:05:24.669605Z","company_name":"Aurora Innovation","company_slug":"aurora-innovation","company_logo_url":"https://www.google.com/s2/favicons?domain=aurora.tech\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/394498a7-3e09-4b7d-9dc4-98c2d5cce6a3"},{"id":"536847ab-380b-4023-a67d-e6f42968d89e","company_id":"ccb23d77-c69e-462b-a941-02ce99527e78","title":"Senior Software Engineer (Data Engineering and Infrastructure)","slug":"senior-software-engineer-data-engineering-and-infrastructure-fbb63209","description":"Who we are \n Aurora’s mission is to deliver the benefits of self-driving technology safely, quickly, and broadly.\n The Aurora Driver  will create a new era in mobility and logistics, one that will bring a safer, more efficient, and more accessible future to everyone.\n  \n At Aurora, you will tackle massively complex problems alongside other passionate, intelligent individuals, growing as an expert while expanding your knowledge. For the latest news from Aurora, visit  aurora.tech  or follow us on  LinkedIn .\n  \n What we are looking for \n Aurora hires talented people with diverse backgrounds who are ready to help build a transportation ecosystem that will make our roads safer, get crucial goods where they need to go, and make mobility more efficient and accessible for all. We are seeking a talented and experienced Software Engineer to join our data engineering and infrastructure team. In this role, you will be a key contributor to the design, development, and maintenance of our data platform, building the scalable and reliable systems that enable our organization to leverage data for insights and product innovation. You will work on the core data lake and data warehouse ecosystem infrastructure, data pipelines, and tools that process data at massive scale, ensuring it is accessible, high-quality, and secure.\n In this role, you will \n \n Design, build, and maintain robust and scalable data pipelines and ETL/ELT processes to ingest, transform, and load data from various sources into our data warehouse.\n Develop and manage data infrastructure components using AWS cloud services and infrastructure-as-code tools like Terraform.\n Collaborate with data scientists, analysts, autonomy engineering teams and product teams to understand their data needs and build solutions that meet their requirements.\n Optimize data processing systems for performance, reliability, and cost-efficiency.\n Implement monitoring, alerting, and logging for data pipelines and infrastructure to ensure operational stability.\n Champion best practices in data governance, data quality, and security.\n Work closely with other senior team members and management to improve the data ecosystem toolings, refine user experience, and continuously polish team roadmap.\n \n Required Qualifications \n \n Master’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience.\n 5+ years of professional experience in software engineering, with a focus on data-related projects.\n Proficiency in at least one programming language commonly used for data engineering (e.g., Python, Go or C++).\n Solid experience with big data processing frameworks like Presto/Trino, EMR, Apache Spark, Flink, Kinesis Data Stream, or similar technologies.\n Hands-on experience with cloud platforms (AWS, GCP, or Azure) and their data services (e.g., S3, Redshift, BigQuery, Glue).\n Strong knowledge of SQL and experience working with relational and NoSQL databases.\n Intermediate knowledge of data analytics infrastructure, including data transformation tools such as DBT and visualization frameworks and tools\n Experience with building and managing data pipelines using an orchestrator like Apache Airflow.\n Able to systematically approach open-ended questions to identify pragmatic data solutions that scale\n Able to work effectively in a highly cross-functional, fast-moving and high-stakes environment\n Proven ability to communicate technical, data-driven solutions to both technical and non-technical audiences across stakeholders\n \n Desirable Qualifications  \n \n Experience with AI toolings, LLM and agentic frameworks\n Experience with data warehousing solutions like Snowflake or data lake architectures.\n Familiarity with modern data stack tools and practices.\n A passion for building elegant, scalable, and maintainable systems.\n Experience using Amazon Web Services (AWS) tools\n \n The base salary range for this position is $146K-$234K per year.  Aurora’s pay ranges are determined by role, level, and location. Within the range, the successful candidate’s starting base pay will be determined based on factors including job-related skills, experience, qualifications, relevant education or training, and market conditions. These ranges may be modified in the future. The successful candidate will also be eligible for an annual bonus, equity compensation, and benefits. \n  #LI-SP1 \n Working at Aurora At Aurora, we bring together extraordinarily talented and experienced people united by the strength of our values. We operate with integrity, set outrageous goals, and build a culture where we win together — all without any jerks.\n We believe in-person work increases collaboration, empathy and our ability to lead effectively. As a result, we operate in a hybrid work environment where Aurorans are in office at least 3 days per week.\n Our Careers page provides insight into what it is like to work at Aurora, and you can find all the latest updates in our Newsroom .\n Our c","salary_min":146000,"salary_max":234000,"location":"Pittsburgh, PA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["agents","data-pipeline","cloud","llm","autonomous-vehicles","infrastructure","data-science","data-engineering"],"apply_url":"https://aurora.tech/jobs/8628064002?gh_jid=8628064002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-13T13:23:27Z","expires_at":"2026-08-15T14:05:24.307008Z","created_at":"2026-07-15T14:06:40.677939Z","updated_at":"2026-07-16T14:05:24.454033Z","company_name":"Aurora Innovation","company_slug":"aurora-innovation","company_logo_url":"https://www.google.com/s2/favicons?domain=aurora.tech\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/536847ab-380b-4023-a67d-e6f42968d89e"},{"id":"58ddb548-32cb-47ff-9778-f85baf797bcf","company_id":"a0000000-0000-0000-0000-000000000003","title":"Senior Data Engineer, Public Sector","slug":"senior-data-engineer-public-sector-8cb646e9","description":"Senior Data Engineer, Public Sector\n As a Data Engineer for the Public Sector business unit, you will build Scale's analytical and business-intelligence infrastructure. Scale's customers process millions of tasks through our APIs, and we're looking for a talented Data Engineer to build scalable solutions to support this growth. You will have widespread purview, with responsibility for understanding, mining, aggregating, and exposing data across the entire business unit to support timely and efficient decision-making and data exploration. You will also implement Scale's data warehouse, data mart, and business intelligence reporting environments, and help users transition their workflows to these systems. \n This role requires collaboration with leadership and cross-functional teams to solve complex problems and develop sustainable, scalable data solutions. Your responsibilities will include both ad-hoc analyses and the creation of core data models and pipelines, directly impacting how Scale operates and evaluates its performance.\n You will:\n \n Work with operations, finance, and engineering to drive the development of pipelines that provide single-source-of-truth foundational accuracy\n Continually improve ongoing data pipelines and simplify self-service support for business stakeholders\n Perform regular system audits, and create data quality tests to ensure complete and accurate reporting of data/metrics\n Develop repeatable, scalable analytical solutions, such as data models, improved pipelines, or better underlying tables\n Have an active Secret security clearance (Top Secret preferred) \n \n Ideally You’d Have:\n \n 5+ years of relevant work experience in a role requiring application of data modeling and analytic skills\n Ability to create extensible and scalable data schema and pipelines that lay the foundation for downstream analysis\n Mastery of SQL and relational databases; experience with programming languages (e.g., Python/R)\n Experience building a reliable transformation layer and pipelines from ambiguous business processes using tools such DBT to create a foundation for data insights\n \n  \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 The base salary range for this full-time position in the location of Washington DC is:\n $200,000 — $250,000 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 working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information. \n We comply with the United States Department of Labor's Pay Transparency provision .  \n PLEASE NOTE: We collect, retain and use personal d","salary_min":200000,"salary_max":250000,"location":"Washington, DC","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["data-pipeline","fine-tuning","data-engineering","data-science"],"apply_url":"https://job-boards.greenhouse.io/scaleai/jobs/4713597005","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-11T02:29:10Z","expires_at":"2026-08-15T14:01:43.155302Z","created_at":"2026-07-12T14:01:20.981859Z","updated_at":"2026-07-16T14:01:43.275975Z","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/58ddb548-32cb-47ff-9778-f85baf797bcf"},{"id":"f85cfe22-626a-4ca6-a996-ecbec9f694e8","company_id":"0565e120-4260-434a-91f5-7009f7fcbbab","title":"Staff Software Engineer, AI Foundations (Agent Optimization)","slug":"staff-software-engineer-ai-foundations-agent-optimization-51cb0084","description":"About Us \n Temporal is an open source programming model that can simplify code, make applications more reliable, and help developers focus on the important things like delivering features faster. We are on a mission to be the reliable foundation of every developer’s toolbox, and are building the team that will make that happen.\n  \n Our values guide us —they are present in how we show up, make decisions, and work together to make an impact. We’re curious, driven, collaborative, genuine and humble.\n  \n Temporal is growing and we are looking for those who share our values, challenge 'standard' thinking, and want to influence our future. If you have a passion for improving the developer experience, building world-class open-source software and communities, and want to be a part of our amazing team, we'd love to hear from you!\n \n About Us \n Temporal is an open source programming model that can simplify code, make applications more reliable, and help developers focus on the important things like delivering features faster. We are on a mission to be the reliable foundation of every developer’s toolbox, and are building the team that will make that happen.\n Our values guide us—they are present in how we show up, make decisions, and work together to make an impact. We’re curious, driven, collaborative, genuine and humble.\n Temporal is growing and we are looking for those who share our values, challenge 'standard' thinking, and want to influence our future. If you have a passion for improving the developer experience, building world-class open-source software and communities, and want to be a part of our amazing team, we'd love to hear from you!\n Summary \n We have an opening to hire a Staff Software Engineer - Agent Optimization \n Temporal provides a reliable foundation powering AI leaders such as OpenAI, NVIDIA, Cursor, Lovable, Replit, and others. Its adoption is expanding to users spanning a broad range of AI applications ranging from agents to data pipelines and everything in between.\n The mission of the AI Foundations team is to accelerate Temporal adoption across the entire ecosystem. Our approach combines a deep understanding of use cases with rigorous application of computer systems and software design principles.\n In this role, you will lead our agent agent optimization efforts. You will design tools and mechanisms to help Temporal users build agents that are optimized for token spend and response time while maintaining result quality. Model routing is a first step, but represents the tip of the iceberg of techniques that we can apply. For example, multi-agent architecture, cache policy, and context management are all relevant. Candidates for this role should have direct experience with this problem domain.\n You will work closely with other AI Foundations team members, e.g., those who focus on agentic development, maintaining a set of agents skills that lift performance of Codex, Claude Code, and similar tools for developers of Temporal applications. Other team members build ecosystem integrations or develop policy and security systems.\n If you thrive on blending theory and practice, then this is the right team for you. We are an action-oriented group that loves to ship fast and solve customer problems. We also seek thorough technical grounding for our work and invest in systems and practices that foster long-term success.\n Most of Temporal’s work is open source—see for yourself here: https://github.com/temporalio [new window]\n What You Will Do \n \n Work as a software engineer\n Maintain and expand a deep understanding of agentic coding\n Design and build agentic coding systems that we can trust to deliver high-quality outputs\n Develop a deep understanding of AI application development patterns and techniques, including emerging approaches and architectures.\n Take end-to-end ownership of new features, working with other teams to deliver exceptional reliability and a great developer experience.\n Work with multiple programming languages: Python and TypeScript, Java, Go.\n Serve as a domain expert on AI design patterns, collaborating with field staff to provide best-practices and canonical examples.\n Work directly with our developer community to debug issues that need expert attention and get feedback on Temporal features and APIs.\n Write public technical documentation describing Temporal concepts and APIs.\n Go the extra mile to support a customer in need, on the rare occasion that our teams’ engineering expertise is needed.\n Travel to meet your coworkers for a week once or twice a year.\n Attend the occasional developer conference to talk about how great Temporal is (optional).\n \n What You Won’t Do \n \n Work as a Data Scientist, Data Analyst, Devops SWE, or SRE.\n Work in an office (unless you want to, but you’d be by yourself). Temporal is a fully-remote company.\n Commit code that’s poorly-tested or works “most of the time”. Temporal aspires to be “Reliable as Gravity”, and we expec","salary_min":224000,"salary_max":302400,"location":"Remote (US)","workplace":"remote","remote_scope":"restricted","job_type":"full-time","experience_level":"lead","tags":["agents","data-pipeline","distributed-systems","generative-ai"],"apply_url":"https://job-boards.greenhouse.io/temporaltechnologies/jobs/5184712007","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-10T23:09:00Z","expires_at":"2026-08-15T14:06:22.870639Z","created_at":"2026-07-12T14:05:18.355113Z","updated_at":"2026-07-16T14:06:23.053204Z","company_name":"Temporal","company_slug":"temporal","company_logo_url":"https://www.google.com/s2/favicons?domain=temporal.io\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/f85cfe22-626a-4ca6-a996-ecbec9f694e8"},{"id":"52c0d743-42dc-4708-98d3-2eda7148a5c5","company_id":"66e863fb-9aaf-40df-996c-eb439e6f857e","title":"Software Engineer","slug":"software-engineer-b563a434","description":"About Glean: \n  \n Glean is the Work AI platform that helps everyone work smarter with AI. What began as the industry’s most advanced enterprise search has evolved into a full-scale Work AI ecosystem, powering intelligent Search, an AI Assistant, and scalable AI agents on one secure, open platform. With over 100 enterprise SaaS connectors, flexible LLM choice, and robust APIs, Glean gives organizations the infrastructure to govern, scale, and customize AI across their entire business - without vendor lock-in or costly implementation cycles. \n  \n At its core, Glean is redefining how enterprises find, use, and act on knowledge. Its Enterprise Graph and Personal Knowledge Graph map the relationships between people, content, and activity, delivering deeply personalized, context-aware responses for every employee. This foundation powers Glean’s agentic capabilities - AI agents that automate real work across teams by accessing the industry’s broadest range of data: enterprise and world, structured and unstructured, historical and real-time. The result: measurable business impact through faster onboarding, hours of productivity gained each week, and smarter, safer decisions at every level. \n  \n Recognized by Fast Company as one of the World’s Most Innovative Companies (Top 10, 2025), by CNBC’s Disruptor 50, Bloomberg’s AI Startups to Watch (2026), Forbes AI 50, and Gartner’s Tech Innovators in Agentic AI, Glean continues to accelerate its global impact. With customers across 50+ industries and 1,000+ employees in more than 25 countries, we’re helping the world’s largest organizations make every employee AI-fluent, and turning the superintelligent enterprise from concept into reality. \n  \n If you’re excited to shape how the world works, you’ll help build systems used daily across Microsoft Teams, Zoom, ServiceNow, Zendesk, GitHub, and many more - deeply embedded where people get things done. You’ll ship agentic capabilities on an open, extensible stack, with the craft and care required for enterprise trust, as we bring Work AI to every employee, in every company. \n About the Role\n Glean Technologies, Inc. has multiple positions available for a Software Engineer. As a Software Engineer, you will help build a software-based platform that can scale indefinitely, including scalable enterprise search solutions. You will work across distributed systems, data pipelines, APIs, and user interfaces to deliver secure, high-quality products that meet customer needs.\n What You Will Do\n \n Develop a software-based platform that can scale indefinitely, including scalable enterprise search solutions.\n Build large-scale fault-tolerant distributed systems, preferably with knowledge of performance benchmarking tools and performance tuning on Linux-based systems.\n Perform thorough code review for peers, including interface design, code quality, and testing strategies.\n Understand customer requirements and implement them in solutions.\n Work closely with the company’s product teams to understand customer requirements and ensure features satisfy those requirements and are delivered effectively with high quality.\n Implement data ingestion pipelines to retrieve data from enterprise data sources and build a secure search index over that data.\n Design and implement user interfaces used by enterprise workers to search enterprise content.\n Design APIs to build other search-based applications.\n \n Who You Are\n \n You have a Master’s degree, or foreign degree equivalent, in Computer Science, Engineering (any field), or a related quantitative discipline, plus three (3) months of experience in the job offered or in any occupation in a related field.\n You have experience working on infrastructure for distributed systems or cloud-native applications, or experience building full-stack applications that span front-end, REST APIs, and application server, or experience training and productionizing machine learning, or information retrieval systems.\n You have experience with Go or C++.\n You have experience with Java.\n You have experience with Python.\n You have experience with TypeScript.\n You have algorithmic design skills.\n You have experience with data analytics.\n You have experience with Node.\n You have experience with Ruby on Rails, Django, or Flask.\n You have experience with React.\n Any suitable combination of education, training, and/or experience is acceptable.\n \n  \n Location: Mountain View, CA. Telecommuting is an option.\n Compensation \u0026 Benefits\n The standard base salary range for this position is $187,741 - $234,000 annually. Compensation offered will be determined by factors such as location, level, job-related knowledge, skills, and experience. Certain roles may be eligible for variable compensation, equity, and benefits.\n  \n We offer a comprehensive benefits package including competitive compensation, Medical, Vision, and Dental coverage, generous time-off policy, and the opportunity to contribute to your 401k ","salary_min":187741,"salary_max":234000,"location":"Mountain View, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["distributed-systems","search","agents","data-pipeline","api-design","cloud","llm"],"apply_url":"https://job-boards.greenhouse.io/gleanwork/jobs/4713145005","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-10T18:21:38Z","expires_at":"2026-08-15T14:04:04.297114Z","created_at":"2026-07-12T14:03:17.754756Z","updated_at":"2026-07-16T14:04:04.428691Z","company_name":"Glean","company_slug":"glean","company_logo_url":"https://www.google.com/s2/favicons?domain=glean.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/52c0d743-42dc-4708-98d3-2eda7148a5c5"},{"id":"08e650fb-0032-430e-b5d5-a6c3007cb351","company_id":"66e863fb-9aaf-40df-996c-eb439e6f857e","title":"Software Engineer","slug":"software-engineer-4d15fbe9","description":"About Glean: \n  \n Glean is the Work AI platform that helps everyone work smarter with AI. What began as the industry’s most advanced enterprise search has evolved into a full-scale Work AI ecosystem, powering intelligent Search, an AI Assistant, and scalable AI agents on one secure, open platform. With over 100 enterprise SaaS connectors, flexible LLM choice, and robust APIs, Glean gives organizations the infrastructure to govern, scale, and customize AI across their entire business - without vendor lock-in or costly implementation cycles. \n  \n At its core, Glean is redefining how enterprises find, use, and act on knowledge. Its Enterprise Graph and Personal Knowledge Graph map the relationships between people, content, and activity, delivering deeply personalized, context-aware responses for every employee. This foundation powers Glean’s agentic capabilities - AI agents that automate real work across teams by accessing the industry’s broadest range of data: enterprise and world, structured and unstructured, historical and real-time. The result: measurable business impact through faster onboarding, hours of productivity gained each week, and smarter, safer decisions at every level. \n  \n Recognized by Fast Company as one of the World’s Most Innovative Companies (Top 10, 2025), by CNBC’s Disruptor 50, Bloomberg’s AI Startups to Watch (2026), Forbes AI 50, and Gartner’s Tech Innovators in Agentic AI, Glean continues to accelerate its global impact. With customers across 50+ industries and 1,000+ employees in more than 25 countries, we’re helping the world’s largest organizations make every employee AI-fluent, and turning the superintelligent enterprise from concept into reality. \n  \n If you’re excited to shape how the world works, you’ll help build systems used daily across Microsoft Teams, Zoom, ServiceNow, Zendesk, GitHub, and many more - deeply embedded where people get things done. You’ll ship agentic capabilities on an open, extensible stack, with the craft and care required for enterprise trust, as we bring Work AI to every employee, in every company. \n About the Role\n Glean Technologies, Inc. has multiple positions available for a Software Engineer. As a Software Engineer, you will help build a software-based platform that can scale indefinitely, including scalable enterprise search solutions. You will work across distributed systems, data pipelines, APIs, and user interfaces to deliver secure, high-quality products that meet customer needs.\n What You Will Do\n \n Develop a software-based platform that can scale indefinitely, including scalable enterprise search solutions.\n Build large-scale fault-tolerant distributed systems, preferably with knowledge of performance benchmarking tools and performance tuning on Linux-based systems.\n Perform thorough code review for peers, including interface design, code quality, and testing strategies.\n Understand customer requirements and implement them in solutions.\n Work closely with the company’s product teams to understand customer requirements and ensure features satisfy those requirements and are delivered effectively with high quality.\n Implement data ingestion pipelines to retrieve data from enterprise data sources and build a secure search index over that data.\n Design and implement user interfaces used by enterprise workers to search enterprise content.\n Design APIs to build other search-based applications.\n \n Who You Are\n \n You have a Bachelor's degree, or foreign degree equivalent, in Computer Science, Engineering (any field), or a related quantitative discipline, and six (6) months of experience in the job offered or in any occupation in related field.\n You have experience working on infrastructure for distributed systems or cloud-native applications, or experience building full-stack applications that span front-end, REST APIs, and application server, or experience training and productionizing machine learning, or information retrieval systems.\n You have experience with Go or C++.\n You have experience with Java.\n You have experience with Python.\n You have experience with TypeScript.\n You have algorithmic design skills.\n You have experience with data analytics.\n You have experience with Node.\n You have experience with Ruby on Rails, Django, or Flask.\n You have experience with React.\n Any suitable combination of education, training, and/or experience is acceptable.\n \n  \n Location: Mountain View, CA. Telecommuting is an option.\n Compensation \u0026 Benefits\n The standard base salary range for this position is $215,000 - $278,900 annually. Compensation offered will be determined by factors such as location, level, job-related knowledge, skills, and experience. Certain roles may be eligible for variable compensation, equity, and benefits.\n  \n We offer a comprehensive benefits package including competitive compensation, Medical, Vision, and Dental coverage, generous time-off policy, and the opportunity to contribute to your 401k plan","salary_min":215000,"salary_max":278900,"location":"Mountain View, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["agents","llm","search","api-design","cloud","data-pipeline","distributed-systems"],"apply_url":"https://job-boards.greenhouse.io/gleanwork/jobs/4713977005","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-10T18:21:37Z","expires_at":"2026-08-15T14:04:04.206223Z","created_at":"2026-07-12T14:03:17.835612Z","updated_at":"2026-07-16T14:04:04.327025Z","company_name":"Glean","company_slug":"glean","company_logo_url":"https://www.google.com/s2/favicons?domain=glean.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/08e650fb-0032-430e-b5d5-a6c3007cb351"},{"id":"34327561-6461-4c2b-9f53-2e7f3bfbf3f1","company_id":"714f360f-a244-487d-b3f0-0c43518a9e66","title":"Staff Data Scientist, Finance \u0026 Business Ops","slug":"staff-data-scientist-finance-business-ops-3620397e","description":"About Pinterest: \n Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.\n Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the  flexibility to do your best work. Creating a career you love? It’s Possible.\n At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI.\n Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here .\n Pinterest is seeking an experienced Staff Data Scientist to join our Finance \u0026 Business Operations team. This is a hybrid data-science / applied-AI / product-engineering role inside Pinterest's CFO organization. It sits at the intersection of forecasting and finance analytics, internal tool-building, and AI adoption — and the person in it is expected to operate across all three.\n The core mandate is to make the CFO org's forecasting and planning work faster, be more  rigorous, and more self-serve. In practice that has meant owning a forecasting product end to end (data pipeline through user-facing UI), partnering directly with Finance, BizOps, and Core/Monetization stakeholders to embed it in their workflows, and turning the company's emerging AI platform capabilities into tools that finance teams actually use day to day.\n This is a high-autonomy, high-trust individual-contributor role with broad cross-functional reach. \n  \n What you'll do: \n \n Own forecasting tooling end to end. Build and maintain the team's primary forecasting workbench — from the underlying data and forecast logic through the interactive web UI that planners use to create, adjust, and review forecasts. This spans baseline vs. adjusted forecast modeling, scenario/delta workflows, backtesting, and diagnostics (year-over-year and month-over-month seasonality, engagement rates, and similar).\n Ship product, not just analysis. Design and build user-facing features: chart and visualization work, guided onboarding, history/audit views, region and time-grain filtering, performance optimization, and the kind of polish and bug-fixing that makes an internal tool feel like a real product. Instrument usage (collect and analyze raw logs) and let adoption data drive the roadmap.\n Drive AI adoption across Finance \u0026 BizOps. Take platform-level AI capabilities and turn them into concrete, trusted tools for finance users. Bring structured business cases (not wishlists) to platform/IT partners, pilot new capabilities, and write the enablement material — walkthroughs, documentation, \"where to get started\" guidance — that gets non-technical teams productive.\n Stay ahead of the AI capability curve. A significant part of this role is forward-looking: continuously read and interpret AI research (papers, model and tooling releases) and translate it into a grounded point of view on what will be possible in the next 6–12 months. Track the engineering roadmap closely, understand what platform capabilities are landing and when, and connect those dots to concrete opportunities for the CFO org — so the team builds for where AI is going, not just where it is today.\n Set AI strategy and guide executives. Turn that capability foresight into strategy: shape the CFO org's AI roadmap, prioritize where to invest, and advise senior leaders and executives on what's real, what's hype, and what to bet on. Communicate complex AI and technical trade-offs in plain, decision-ready terms, and act as a trusted technical advisor in executive conversations.\n Deliver recurring finance analytics. Support core CFO-org deliverables: budget-vs-actuals (BVAs), variance commentary, executive slide/deck preparation, and metric diagnostics (e.g., MAU and revenue diagnostics), including catching and resolving data-quality issues.\n Partner broadly and communicate clearly. Work directly with Finance, BizOps, Monetization, and platform/IT stakeholders. Translate ambiguous business questions into tooling and analysis, post clear release notes and stakeholder updates, and run live walkthroughs and training sessions.\n Set technical and analytical standards. raise the bar on rigor (validation, backtesting, sound metric definitions), make pragmatic build-vs-buy and scope calls, and create artifacts and documentation durable enough to outlive any single contri","salary_min":164695,"salary_max":339078,"location":"San Francisco, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["agents","data-pipeline","llm","data-science"],"apply_url":"https://www.pinterestcareers.com/jobs/?gh_jid=8036273","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-10T15:59:18Z","expires_at":"2026-08-15T14:09:23.913817Z","created_at":"2026-07-12T14:07:55.214517Z","updated_at":"2026-07-16T14:09:24.031949Z","company_name":"Pinterest","company_slug":"pinterest","company_logo_url":"https://www.google.com/s2/favicons?domain=www.pinterest.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/34327561-6461-4c2b-9f53-2e7f3bfbf3f1"},{"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","data-pipeline","embeddings","mlops","cloud","agents","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":"2026-08-15T14:09:59.865872Z","created_at":"2026-07-10T14:08:46.130561Z","updated_at":"2026-07-16T14:09:59.981772Z","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":"983ab9e8-9226-4b77-a521-b03c442804e8","company_id":"6734f15a-40ed-4186-ae4a-d774c655ae58","title":"Senior Director, Software Development, Test Automation","slug":"senior-director-software-development-test-automation-8909403d","description":"Your Impact at LILA \n The Role \n We're hiring a Senior Director, Software Development, Test Automation Systems to architect and build Lila's test automation platform and quality engineering practice for our AI-powered scientific and lab automation products. Reporting to the VP of Engineering, you'll own the test automation system, CI/CD test infrastructure, AI-driven test tooling, and the eval discipline that hold the bar across our SDLC.\n This is a builder-leader role. You will drive the quality vision, write requirements, make sharp build-vs-buy calls, drive execution, and build and lead a small (3–5 person) team that delivers leverage. The operating model is federated: you own the platform, standards, and metrics; engineering teams own test execution. You scale through tooling and influence.\n As you scale into this role, you'll also stand up the QC framework for our lab automation system — the validation patterns, harnesses, and contracts that science operations teams will operate day-to-day. Data integrity and ALCOA+ compliance are foundational to everything you build.\n What You'll Be Building \n What You'll Do \n Architect and ship the test automation platform \n \n Design and build the test automation platform — frameworks, fixtures, golden datasets, test orchestration, and reporting — that the engineering org adopts by default\n Set standards across unit, integration, contract, end-to-end, regression, performance, and chaos testing for backend services, the frontend monorepo, and data pipelines\n Treat platform adoption, flake rate, and time-to-signal as first-class engineering metrics\n \n Make build-vs-buy decisions with conviction \n \n Own the buy/build/borrow strategy across test infrastructure, eval platforms, browser/device clouds, observability, and lab QC tooling\n Justify every choice with TCO, signal quality, integration cost, and time-to-leverage — and revisit decisions as the org and tech landscape evolve\n Bias toward leverage: buy commodity capabilities, build the differentiators (Lila-specific AI evals, lab QC, scientific data integrity)\n \n Modernize CI/CD for fast, reliable signal \n \n Own the test execution layer of CI/CD: parallelization, caching, hermetic environments, ephemeral preview envs, and affected-only test selection across our Nx monorepo/microservices.\n Build retry, quarantine, and impact-analysis systems so signal stays sharp as the org scales\n Drive change-failure rate, MTTR, Test effectiveness, pipeline efficiency, coverage, and PR-to-prod lead time as outcomes\n \n Drive AI-driven test automation \n \n Apply LLMs across the full test lifecycle: test generation from specs and PRs, self-healing UI tests, synthesis, visual regression with vision models, and AI-assisted failure triage\n Validate every AI-generated test through evals — no LLM-authored test ships without proof it doesn't degrade signal\n Establish the eval discipline for Lila's AI/agent stack: golden datasets, rubrics, regression suites, offline + online evaluation pipelines\n \n Define and operate the quality metrics system \n \n Define quality SLOs and adoption metrics by team and service: coverage, escape rate, MTTR, change-failure rate, eval pass rate, lab QC violation rate\n Build dashboards that make quality visible from PR to executive review\n Apply Google SRE practices to prioritize where investment goes\n \n Mid-long term - Stand up the QC framework for lab automation \n \n Design the validation framework, harnesses, and contracts that lab and Science Ops teams will operate\n Embed ALCOA+ principles: data integrity, audit trails, lineage from sample → instrument → output\n Partner with Research Ops on pre-flight, in-flight, and post-flight validation patterns for autonomous lab execution\n \n Lead and coach across the engineering org \n \n Build a 3–5 person team of test automation engineers focused on platform leverage, not on writing tests for other teams\n Coach engineering teams on test design, quality investments, and adoption — make it cheaper to test well than to ship blind\n Translate UX and customer issues into testable contracts and platform improvements\n \n First 6–12 Month Outcomes \n \n First 90 days: Establish baselines — flake rate, time-to-signal, change-failure rate, coverage, and current build-vs-buy footprint — and publish a quality scorecard with the first set of SLOs. Hire or onboard the initial 1–2 platform engineers.\n By 6 months: Ship v1 of the test automation platform adopted by at least one flagship engineering team by default; land CI/CD test-execution improvements (parallelization, affected-only selection, flake quarantine) with measurable time-to-signal reduction. Stand up the eval discipline (golden datasets, rubrics, regression suites) for the AI/agent stack.\n By 12 months: Drive default platform adoption across the engineering org; demonstrate AI-driven test automation in production with eval-gated rollout. 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