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Our mission is simple but profound—give time back to clinicians so they can focus on what matters most: caring for patients.\n Today, doctors spend hours navigating complex electronic health record (EHR) systems—modern versions of paper charts that are often unintuitive, fragmented, and time-consuming. Suki changes that. Clinicians using Suki already spend 70% less time on administrative work, and we’re just getting started.\n Our platform is the foundation of everything we do. As we scale AI-powered capabilities across voice, ambient, and enterprise experiences—and extend them to health system partners, EHR ecosystems, and third-party developers—we need a seasoned platform product leader to define and drive the next generation of our technical platform strategy.\n The Role \n As Head of Platform Products, you will own the product vision, strategy, and roadmap for Suki’s core platform—the APIs, services, and integration layers that enable external partners to build on top of our technology.\n You will lead a team of platform product managers and serve as a strategic partner to Engineering, Commercial, and executive leadership. Your work will determine how Suki’s AI, speech, and clinical intelligence capabilities are architected, scaled, and delivered to the broader healthcare ecosystem.\n This is a rare opportunity to shape the platform that underpins an AI-first healthcare company—and to set a new standard for how health technology platforms are built and scaled.\n What You’ll Do \n Define Platform Vision \u0026 Strategy \n \n Own and drive a clear, compelling multi-year platform product strategy that enables Suki’s product portfolio and ecosystem growth\n Define the platform’s service architecture, API strategy, and extensibility model to support current products and future innovation\n Translate complex AI/ML, NLP, and speech capabilities into well-architected, reusable platform services\n \n Drive Interoperability \u0026 Health Data Strategy \n \n Own the strategy for integrations including EHR (Athena and others), ensuring deep, reliable, and scalable connectivity\n Define the approach to health data standards (FHIR, HL7, CDA) and ensure the platform is built for healthcare-grade interoperability\n Partner with compliance and security teams to maintain HIPAA compliance, SOC 2 certification, and enterprise-grade data governance across the platform\n \n Scale AI \u0026 ML Platform Capabilities \n \n Work closely with AI/ML leadership to productize core capabilities—ambient AI, clinical NLP, medical speech recognition, and generative AI—as scalable platform services\n Enable rapid experimentation and deployment of new AI capabilities across product surfaces\n \n Build for the Ecosystem \n \n Define and execute the developer platform and partner integration strategy, including APIs, SDKs, documentation, and developer experience\n Work with business development and partnerships teams to identify and enable high-value platform use cases for health systems, EHR vendors, and third-party developers\n Build the foundation for a platform ecosystem that creates compounding value for Suki and its partners\n \n Be a Strategic Product Partner \n \n Partner closely with the Chief Product Officer, Engineering leadership, and Commercial leadership to align platform investments with company strategy and product roadmap\n Ground platform decisions in data, customer insights, technical feasibility, and business impact\n Drive prioritization and trade-off decisions across competing platform demands from internal teams and external partners\n \n Build and Scale a World-Class Team \n \n Lead, mentor, and grow a high-performing platform product management team\n Foster a culture of technical excellence, customer empathy, accountability, and impact\n Identify and close gaps in skills, tools, processes, and operating models as the platform organization scales\n \n What We’re Looking For \n \n 12+ years of product management experience, with 5+ years in senior/leadership roles owning platform, infrastructure, or developer-facing products\n Deep expertise in platform product management: APIs, developer experience, data platforms, integration architectures, and service-oriented systems\n Strong background in healthcare technology, with hands-on experience navigating EHR ecosystems, health data standards (FHIR, HL7), and regulatory requirements (HIPAA, SOC 2)\n Experience productizing AI/ML capabilities at scale—ideally in NLP, speech, or applied clinical AI\n Proven track record of building and scaling platform product teams in high-growth, product-led organizations\n Technically fluent: comfortable engaging deeply with engineering and data science teams on architecture, systems design, and technical trade-offs\n Strong analytical and strategic thinking skills, with the ability ","salary_min":300000,"salary_max":350000,"location":"Redwood City, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["generative-ai","speech","nlp","healthcare"],"apply_url":"https://www.suki.ai/open-positions?gh_jid=7701264003","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-05T18:39:48Z","expires_at":"2026-11-13T16:59:13.387627Z","created_at":"2026-10-14T15:22:45.229335Z","updated_at":"2026-10-14T16:59:13.390591Z","company_name":"Suki","company_slug":"suki","company_logo_url":"https://www.google.com/s2/favicons?domain=suki.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/2dfdf022-1baf-4133-a9ec-68fda0e96567"},{"id":"e94804b6-8f44-4fe0-bdcb-431f0e4dc939","company_id":"dc461dc0-20f9-4429-a009-6cb473fc466c","title":"Finance Engineer","slug":"finance-engineer-f3636cea","description":"Why AssemblyAI \n AssemblyAI builds the best-in-class Voice AI models powering the next generation of voice applications. Our models serve 600M+ inference calls monthly, process 1M+ hours of audio daily, and power 2 billion+ end-user experiences. The Voice AI space is at an inflection point; we’re looking for folks truly excited to join a small team and help define the future of the industry.\n We are one of the most capital-efficient AI companies on the planet - with under 100 people generating roughly $600K ARR per employee, we sit among the top 5 most revenue-dense teams within the fastest-growing AI companies today. That's not an accident; it's a deliberate choice to stay lean, move fast, and give every person on the team outsized ownership and impact. With thousands of customers including Granola, Fireflies, Figure AI, and CallRail, the company has real scale - processing over 2 million hours of audio daily and handling more than 1 million API calls every day. This is a rare growth-stage opportunity where the business is proven and the trajectory is steep, but the team is still small enough that your fingerprints are on everything.\n If you've ever felt buried under layers of bureaucracy, starved of real ownership, or frustrated watching your work disappear into a slow-moving org, AssemblyAI is built differently. The company operates as a true meritocracy, with no heavy planning or approval processes and no gatekeeping on the tools or information you need. For anyone who genuinely cares about voice AI, not as a trend to chase, but as a technology to build,  this is the place where the most interesting problems at the most interesting scale are being solved by a team small enough that you'll actually know everyone's name.\n We’re committed to creating a space where our employees can bring their full selves to work and have equal opportunity to succeed. No matter your race, gender identity or expression, sexual orientation, religion, origin, ability, age, veteran status, if joining this mission speaks to you, we encourage you to apply!\n About the role: \n We're looking for a Finance Engineer to join our Finance team, building the data pipelines, dashboards, and automation that run the finance function and the revenue operations around it, from deal desk to sales compensation. Our goal is to operate finance as a small, senior team that runs on systems rather than headcount — and how well we do that depends on how quickly anyone here can get a trusted number on unit economics, cash burn, or technology spend and act on it. Building that capability is the heart of this role. You'll be working inside the numbers you're automating, not alongside them.The ideal candidate is an engineer first: strong data engineering fundamentals across SQL, Python, warehouse modeling, and orchestration, combined with enough finance and operational fluency to model revenue, cost, and margin without hand-holding. Experience building internal tools and agent workflows that non-engineers rely on daily is what sets this candidate apart.\n This is a cross-functional role. You'll work closely with the VP Finance, our Controller, sales leadership, and engineering and infrastructure leadership — not as a handoff point, but as the person who learns enough of each domain to follow a number back to its source. At times you'll build the model, run the analysis, and present the finding yourself, both to deliver impact directly and to learn what's worth automating next. The bar is someone who understands the decision a number is meant to support, measures it from the outset, and would rather find out a model was wrong in a week than at quarter close. That discipline is what turns cross-functional ownership into an advantage.\n The role is embedded within the Finance team and reports to the VP Finance.\n What You’ll Do: \n \n Own unit economics — build and maintain cost-to-serve, gross margin, and contribution models by product, customer, and workload, rebuilt from source data rather than spreadsheets.\n Own budgeting for the technology organization: cloud and GPU/TPU spend attribution, vendor and capacity forecasting, and the models engineering leadership uses to plan.\n Build and run finance dashboarding — a single source of truth for burn, runway, margin, and company KPIs that the leadership team and board can trust.\n Automate budget-vs-actuals: live department-level views and overspend alerts that make budget and margin targets enforceable without manual chasing.\n Build the deal desk framework: pricing and discount guardrails derived from the margin model, automated quote and order-form generation, and routing so only non-standard deals need escalation — raising deal throughput without finance in the loop on every deal.\n Automate sales compensation: implement a comp tool and the pipelines behind it so statements, accelerators, and disputes run from CRM and billing data instead of spreadsheets.\n Design and ship finance agents and inter","salary_min":160000,"salary_max":240000,"location":"United States","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["speech","llm","payments","data-pipeline"],"apply_url":"https://job-boards.greenhouse.io/assemblyai/jobs/4737169005","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-09-24T16:19:51Z","expires_at":"2026-11-13T16:55:57.239469Z","created_at":"2026-10-14T15:20:06.621791Z","updated_at":"2026-10-14T16:55:57.242473Z","company_name":"AssemblyAI","company_slug":"assemblyai","company_logo_url":"https://www.google.com/s2/favicons?domain=assemblyai.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/e94804b6-8f44-4fe0-bdcb-431f0e4dc939"},{"id":"c6935fc0-f819-4d38-9cd6-92fd0e613137","company_id":"099735cb-7b94-42a0-a625-8674b74008ad","title":"Senior Applied Research Scientist - Personalization","slug":"senior-applied-research-scientist-personalization-b6e11c0d","description":"The Personalization team makes deciding what to play next easier and more enjoyable for every listener. From Blend to Discover Weekly, we're behind some of Spotify's most-loved features. We built them by understanding the world of music and podcasts better than anyone else. Join us and you'll keep millions of users listening by making great recommendations to each and every one of them.\n\nWithin Personalization, the Speak Team owns the development of Spotify's state-of-the-art speech models, contributing to speech recognition, speech synthesis, and speech-to-speech models. We craft voice models that match human-level emotional expressiveness, so we can deeply engage our listeners and support creators at scale. Our groundbreaking work on speech synthesis relies on state-of-the-art deep learning methods and evaluation techniques, highly efficient data processing and model serving, and capturing audio of outstanding quality from our voice talent pool.\n\nWe're looking for a senior applied research scientist with experience in developing novel ML techniques and architectures and with a strong interest in working across a full production pipeline to produce state-of-the-art generative conversational speech-to-speech models. You'll collaborate with our engineering teams to help develop our production pipelines, explore new ideas and methods to improve quality, understanding and realism, as well as push the frontiers of what is possible with our speech technology.\n","salary_min":169157,"salary_max":241653,"location":"New York, NY","workplace":"remote","remote_scope":"unknown","job_type":"full-time","experience_level":"senior","tags":["deep-learning","mlops","speech","research"],"apply_url":"https://jobs.lever.co/spotify/6eb9ce0e-5372-4a4f-b2fa-d005f9426750/apply","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-09-21T17:45:52.302Z","expires_at":"2026-11-13T16:58:03.593748Z","created_at":"2026-10-14T15:21:43.685761Z","updated_at":"2026-10-14T16:58:03.596656Z","company_name":"Spotify","company_slug":"spotify","company_logo_url":"https://www.google.com/s2/favicons?domain=www.spotify.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/c6935fc0-f819-4d38-9cd6-92fd0e613137"},{"id":"c86f5174-eb44-436e-92ad-1d161af54673","company_id":"95fc9d4d-801c-4800-88aa-1301b340d8f5","title":"Member of Technical Staff, Infrastructure Engineer","slug":"member-of-technical-staff-infrastructure-engineer-d6cd8dac","description":"Vapi (/ˈVɑːpi/):\n\n - Voice AI that resolves, not transfers\n\n - Powering 1 billion calls for companies like Amazon Ring, Intuit, ServiceTitan, and New York Life\n\n - Trusted by 1 million developers building the future of voice agents\n\n - Backed by Peak XV, Bessemer, Kleiner Perkins, M12, Y Combinator, and more with $72M raised\n\n - Try talking to Vapi now! https://vapi.ai/\n\n\nVAPI (/ˈVⱭːPI/):\n\n - Voice AI that resolves, not transfers\n\n - Powering 1 billion calls for companies like Amazon Ring, Intuit, ServiceTitan, and New York Life\n\n - Trusted by 1 million developers building the future of voice agents\n\n - Backed by Peak XV, Bessemer, Kleiner Perkins, M12, Y Combinator, and more with $72M raised\n\n - Try talking to Vapi now! https://vapi.ai/\n\n\n\n\nWHY THIS ROLE:\n\n - Vapi’s real-time voice platform depends on core infrastructure across compute, storage, networking, and telephony. As usage grows, reliability has to be designed into the systems our customers depend on.\n\n - We’re adding a dedicated SRE profile to our five-person Infrastructure team. We need a software-first engineer who can build tooling and automation, improve observability, and turn operational lessons into lasting engineering improvements.\n\n - This role has a distinct focus from our broader Infrastructure Engineer role because it requires deep reliability and operability judgment. You’ll join a calibrated team and work on latency-sensitive systems at meaningful scale. This role is based in San Francisco.\n\n\n\n\nWHAT YOU’LL DO:\n\n - 30 Days: Learn Vapi’s architecture, production environment, incident history, and reliability practices. Build context with the Infrastructure and product engineering teams, then contribute an initial operational or reliability improvement.\n\n - 60 Days: Own a reliability workstream across observability, incident response, capacity, performance, or production automation. Reduce manual work and improve how the team detects, understands, and responds to failures.\n\n - 90 Days: Become the go-to owner for a meaningful part of Vapi’s reliability surface. Deliver a durable improvement to failure prevention or recovery, and propose a roadmap for the next reliability investments.\n\n\n\n\nWHO YOU ARE:\n\n - You are a senior or staff-level software engineer with meaningful SRE, production engineering, or infrastructure experience in distributed systems.\n\n - You write production-quality software and have built reliability tooling or automation yourself, rather than relying only on operational process.\n\n - You have deep experience with observability, incident response, failure analysis, capacity, and the practices that keep production systems healthy.\n\n - You are comfortable with Kubernetes, networking, and cloud infrastructure, and you can debug across application and infrastructure boundaries.\n\n - You reason clearly about failure modes and can balance reliability investments with product and engineering velocity.\n\n - Experience with real-time networking or telephony, Envoy, Postgres, Redis, Kafka, Aurora, ClickHouse, or a Google-style SRE environment is a strong plus.\n\n\n\n\nHOW WE WORK: \n\n - Build something worthy of love\n   \n   - Craft matters. We aim to build products and experiences customers genuinely love, not just tolerate.\n\n - Commit and follow through\n   \n   - We finish what we start and build trust by being people others can count on.\n\n - Why not today?\n   \n   - We value urgency and momentum. The fastest path to customer value usually wins.\n\n - Seek raw input\n   \n   - We go directly to customers, data, and teammates instead of relying on summaries or assumptions.\n\n - It’s our problem\n   \n   - We operate as one team. We share credit, own mistakes together, and support each other when things get hard.\n\n - Be direct and kind\n   \n   - We give feedback clearly, respectfully, and without delay.\n\n\n\n\nWHY VAPI:\n\n - Generational impact: Build the human interface for every business\n\n - Ownership culture: 70% of the company are previous founders\n\n - Kind team: The founders, Jordan and Nikhil, are Canadians\n\n - Tier-1 Investors: YC, KP seed, Bessemer Series A\n\n\n\n\nWHAT WE OFFER:\n\n - Real stake: We offer a base salary of $280,000 to $314,000 and excellent equity ownership\n\n - Comprehensive health coverage: medical, dental, and vision plans\n\n - Team love: We love hanging out, and we do quarterly off-sites\n\n - Flexible time off: take what you need\n\n - More: catered meals, transportation, gym, and a $10k annual L\u0026D budget","salary_min":280000,"salary_max":314000,"location":"San Francisco, CA","workplace":"remote","remote_scope":"unknown","job_type":"full-time","experience_level":"lead","tags":["distributed-systems","speech","cloud","infrastructure"],"apply_url":"https://jobs.ashbyhq.com/vapi/a3bde43c-4762-4cf2-86f5-464abd4a78e6/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-09-12T04:31:34.84Z","expires_at":"2026-11-13T16:59:09.343941Z","created_at":"2026-09-12T13:41:37.448541Z","updated_at":"2026-10-14T16:59:09.346825Z","company_name":"Vapi","company_slug":"vapi","company_logo_url":"https://www.google.com/s2/favicons?domain=vapi.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/c86f5174-eb44-436e-92ad-1d161af54673"},{"id":"72c4ac64-99b6-466c-9fdb-dc87568a7b45","company_id":"dc461dc0-20f9-4429-a009-6cb473fc466c","title":"Security Operations Engineer","slug":"security-operations-engineer-3e7f8f2e","description":"Why AssemblyAI \n AssemblyAI builds the best-in-class Voice AI models powering the next generation of voice applications. Our models serve 600M+ inference calls monthly, process 1M+ hours of audio daily, and power 2 billion+ end-user experiences. The Voice AI space is at an inflection point; we’re looking for folks truly excited to join a small team and help define the future of the industry.\n We are one of the most capital-efficient AI companies on the planet - with under 100 people generating roughly $600K ARR per employee, we sit among the top 5 most revenue-dense teams within the fastest-growing AI companies today. That's not an accident; it's a deliberate choice to stay lean, move fast, and give every person on the team outsized ownership and impact. With thousands of customers including Granola, Fireflies, Figure AI, and CallRail, the company has real scale - processing over 2 million hours of audio daily and handling more than 1 million API calls every day. This is a rare growth-stage opportunity where the business is proven and the trajectory is steep, but the team is still small enough that your fingerprints are on everything.\n If you've ever felt buried under layers of bureaucracy, starved of real ownership, or frustrated watching your work disappear into a slow-moving org, AssemblyAI is built differently. The company operates as a true meritocracy, with no heavy planning or approval processes and no gatekeeping on the tools or information you need. For anyone who genuinely cares about voice AI, not as a trend to chase, but as a technology to build,  this is the place where the most interesting problems at the most interesting scale are being solved by a team small enough that you'll actually know everyone's name.\n We’re committed to creating a space where our employees can bring their full selves to work and have equal opportunity to succeed. No matter your race, gender identity or expression, sexual orientation, religion, origin, ability, age, veteran status, if joining this mission speaks to you, we encourage you to apply!\n About the role: \n AssemblyAI runs a mature, multi-framework security and compliance program—including SOC 2 (all trust criteria), ISO 27001, and PCI 4.0—that protects the infrastructure and customer data behind our industry-leading Voice AI API. We're hiring a Security Operations Engineer to join our IT \u0026 Security team and take day-to-day ownership of the operational backbone of that program.\n This role is centered on security operations and GRC: running compliance audit cycles end to end, gathering and organizing evidence, enforcing and verifying controls, executing access reviews, managing vulnerability triage and remediation follow-up, and responding to customer security questionnaires. It's the work that turns a security program on paper into one that demonstrably runs. You'll also have room to grow the technical side of the role. We automate wherever we can, and you'll be encouraged to build scripts, integrations, and tooling that reduce manual toil and improve the program.\n This is a high-ownership role on a small team. You'll work closely with engineers across the company, partner with sales and legal on customer-facing security needs, and have a direct hand in how AssemblyAI enforces security across its products, infrastructure, and internal tools—including a rapidly growing landscape of agentic AI development.\n What You'll Do: \n \n Drive SOC 2, ISO 27001, PCI 4.0, and other compliance audit cycles: gather and organize evidence, document, design, and build controls, coordinate directly with auditors through fieldwork, and collaborate with internal teams on remediation.\n Own the compliance automation platform (Vanta): monitor control status, chase down failing checks, keep integrations healthy, and update the risk register as the business and infrastructure evolve.\n Run vendor and third-party risk reviews, security assessments of new tools, periodic re-reviews, and track subprocessor and vendor inventories.\n Partner with sales and legal responding to customer and vendor security questionnaires, RFP security sections, and trust-and-safety inquiries.\n Drive vulnerability triage and prioritization across teams, tracking remediation against SLAs and reporting metrics to stakeholders.\n Monitor and respond to alerts from endpoint, cloud, identity, and application security tools; investigate, escalate, and close the loop.\n Support incident response for security events: evidence collection, timeline construction, documentation, and tracking of post-incident action items.\n Maintain and improve security runbooks, process documentation, and operational playbooks.\n Build automation to reduce the manual burden via scripts, integrations, reporting, and tooling.\n \n What You'll Need: \n \n 3+ years of experience in security operations, GRC, IT security, or a related role\n 2+ years of experience with compliance audit cycles—you've gathered evidence, documented controls, and w","salary_min":180000,"salary_max":220000,"location":"United States","workplace":"remote","remote_scope":"restricted","job_type":"full-time","experience_level":"senior","tags":["llm","security","cloud","agents","speech","code-generation"],"apply_url":"https://job-boards.greenhouse.io/assemblyai/jobs/4732736005","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-09-10T16:21:07Z","expires_at":"2026-11-13T16:55:57.250194Z","created_at":"2026-09-12T13:34:49.099908Z","updated_at":"2026-10-14T16:55:57.253186Z","company_name":"AssemblyAI","company_slug":"assemblyai","company_logo_url":"https://www.google.com/s2/favicons?domain=assemblyai.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/72c4ac64-99b6-466c-9fdb-dc87568a7b45"},{"id":"ae269001-d563-42b0-aff4-0a380150a19b","company_id":"776e5e7d-beba-4889-a481-6d9d7c3af325","title":"Research Engineer, Audio and Speech","slug":"research-engineer-audio-and-speech-6d6a519f","description":"About Decagon\n\nDecagon is the leading conversational AI platform empowering every brand to deliver concierge customer experiences.\n\nOur technology enables industry-defining enterprises like Avis Budget Group, Block’s Cash App and Square, Chime, Oura Health, and Hunter Douglas to deploy AI agents that power personalized, deeply satisfying interactions across voice, chat, email, SMS, and every other channel.\n\nWe’re building a future where customer experiences are being redefined from support tickets and hold music to faster resolutions, richer conversations, and deeper relationships. We’re proud to be backed by world-class investors who share that vision, including a16z, Accel, Bain Capital Ventures, Coatue, and Index Ventures, along with many others.\n\nWe’re an in-office company, driven by a shared commitment to excellence and velocity. Our values — Just Get It Done, Invent What Customers Want, Winner’s Mindset, and The Polymath Principle — shape how we work and grow as a team.\n\n\n\nAbout the Team\n\nRead more about the Speech Research Team's work:\n\n - https://decagon.ai/blog/audio-native-semantic-speaker-change-detection\n\n - https://decagon.ai/blog/scaling-real-time-tts-inference\n\n - https://decagon.ai/blog/teaching-flow-matching-tts-with-rl\n\nThe Research team develops the model and decision-making stack that powers Decagon’s conversational agents for enterprise support. We research, adapt, and implement state-of-the-art techniques in model training, prompting, orchestration, and evaluation in order to make our agents more accurate, robust, and efficient in real-world deployments.\n\nOur goal is to push the frontier of applied conversational AI: agents that reliably understand nuanced intent, track long context, and take the right actions under uncertainty. We measure success the way customers feel it: higher resolution rates, better user satisfaction, and consistent behavior at scale.\n\n\n\nAbout the Role\n\nAs a Research Engineer focused on Audio and Speech, you’ll be responsible for building the models and agent harnesses that power Decagon’s real-time voice agents and taking them all the way from idea to production. Your work will advance multimodal and full-duplex systems that can listen, reason, speak, and respond naturally in real time.\n\nWe’re looking for strong engineers who want to build the next generation of AI voice agents. People here own their work end-to-end, ship real improvements, and are trusted to make high-impact technical decisions.\n\n\n\nIn this role, you will\n\n - Design and build next-generation agent harnesses optimized for streaming speech, turn-taking, interruptions, overlapping speech, and continuous interaction\n\n - Research and train multimodal and full-duplex models that jointly understand audio, reason, and generate speech\n\n - Improve speech recognition, voice activity detection, endpointing, and speech generation across diverse speakers, environments, domains, and languages\n\n - Build evaluations and use production calls to ship measurable improvements in accuracy, latency, naturalness, and task outcomes\n\n - Optimize end-to-end inference for responsiveness, throughput, stability, and cost, partnering with Voice Platform and Infrastructure teams to deploy at scale\n\n\n\nYour background looks something like this\n\n - 2+ years of experience in speech, audio ML, multimodal ML, or production machine learning\n\n - Experience developing or adapting autoregressive, diffusion, flow-matching, or codec-based speech models\n\n - Hands-on experience with streaming agent systems, low-latency inference, production model serving, and evaluation on real-world audio\n\n - Fluency in Python and a modern deep-learning framework such as PyTorch, with strong foundations in machine learning and signal processing\n\n - A track record of taking research ideas from prototype to reliable, measurable production impact\n\n\nEven better if you have\n\n - Familiarity with speech-to-speech or full-duplex models\n\n - Experience with telephony, multilingual speech, noisy-channel robustness, speaker adaptation, or expressive speech generation\n\n\n\nCompensation\n\n$200K – $400K + Offers Equity\n\n\n\nBenefits\n\nWe proudly offer the following benefits for our full-time employees:\n\n - Medical, Dental, and Vision benefits for you and your family\n\n - Life Insurance and Disability Benefits\n\n - Retirement Plan (e.g., 401K, pension)\n\n - Parental Leave\n\n - Fertility and family building benefits through Carrot\n\n - Monthly stipend to support your wellness, lifestyle, and work-life balance\n\n - Daily lunches and snacks in the office to keep you at your best\n\n - Take what you need vacation policy (subject to local requirements; UK employees receive 25 days of statutory leave)\n\nThese benefits are described in more detail in Decagon’s policies, may vary by location, and can change at any time according to applicable compensation and benefits plans.","salary_min":200000,"salary_max":400000,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"junior","tags":["pytorch","mlops","search","speech","agents","research"],"apply_url":"https://jobs.ashbyhq.com/decagon/69fd28a8-0de2-45a5-9b98-33725515add4/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-09-04T23:09:32.292Z","expires_at":"2026-11-13T16:57:20.719626Z","created_at":"2026-09-05T13:36:51.304797Z","updated_at":"2026-10-14T16:57:20.722639Z","company_name":"Decagon","company_slug":"decagon","company_logo_url":"https://www.google.com/s2/favicons?domain=decagon.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/ae269001-d563-42b0-aff4-0a380150a19b"},{"id":"9a398fdb-238a-481a-bd92-943d478410ae","company_id":"2ca4efa5-edc2-4352-a597-ea27086e1e5b","title":"Senior Software Engineer II, AI Labs \u0026 Foundations","slug":"senior-software-engineer-ii-ai-labs-foundations-a4264177","description":"We're transforming the grocery industry \n At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers. \n Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table.\n Instacart is a Flex First team \n There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work. \n Overview\n Join Instacart's mission to transform grocery shopping through frontier AI. As a Senior Software Engineer on AI Labs \u0026 Foundations, you will design, build, and operate the high-scale production systems that power our most ambitious AI experiences—from Cart Assistant, our conversational shopping agent, to voice AI interactions and beyond. This is a high-impact opportunity to work at the intersection of robust software engineering and cutting-edge production AI/ML, directly shaping products used by millions of customers every day.\n We are hiring a Senior Software Engineer who will participate in the design and delivery of production AI systems, identify high-leverage technical opportunities, and contribute hands-on to AI-native products across Instacart's platform. We value bottom-up ideas, high engineering quality, and close partnership with Product, Data Science, ML, and Infrastructure teams. If you enjoy inventing, navigating ambiguity, prototyping fast, and turning wild ideas into real, scalable products, this is the team for you.\n AI Labs \u0026 Foundations sits at the intersection of frontier AI research and production engineering. Our portfolio spans the full stack of AI innovation at Instacart, including building and launching Cart Assistant, pioneering voice AI interactions, and constructing the foundational systems that power these cutting-edge experiences. We are a fast-moving, collaborative team that thrives on 0-to-1 thinking, shares learnings openly, and ships with urgency by prototyping fast and testing rigorously.\n About the Job\n \n Design, build, and operate production AI-powered systems and agentic experiences (including Cart Assistant and voice AI) that directly impact how millions of customers shop.\n Build foundational systems for cutting-edge AI experiences, ranging from embedding infrastructure and voice AI pipelines, to client facing components and integrations, by prototyping bold ideas and productizing what works.\n Integrate foundation models via APIs and open-source frameworks; apply techniques like retrieval-augmented generation and vector search where appropriate.\n Own projects end-to-end: requirements, technical design, implementation, testing, deployment, observability, and iterative improvement focused on reliability, latency, and cost efficiency.\n Collaborate with cross-functional partners in product, design, data science, and infrastructure to ship AI features end-to-end.\n Drive engineering excellence, including thoughtful system design, rigorous code review, and technical leadership that includes defining and promoting best practices for AI/ML production engineering across the team.\n \n About You\n Minimum Qualifications: \n \n Proven senior software engineer who has built, shipped, and operated production systems at scale. You make architectural calls, own what you build, and deliver through ambiguity.\n Hands-on experience with AI or ML in production. You've shipped LLM-powered features or integrated foundation model APIs into a live product, demonstrating the necessary expertise at the intersection of robust software engineering and deep production ML.\n Experience owning services end-to-end, including CI/CD, automated testing, observability (logging, metrics, tracing), and on-call participation.\n Strong communicator who partners well across disciplines - you want to get to the right answer, not just defend the first one.\n Golang, Python, or Typescript language experience \n Excitement and ability to leverage cutting-edge development tools, including AI assistance (e.g., Copilot, Cursor, Claude), to maximize velocity.\n \n Preferred Qualifications: \n \n 5 to 8+ years of industry experience.\n A track record of 0-to-1 work taking unconventional ideas from prototype through rapid iteration to production.\n Experience building conversational agents, multi-tur","salary_min":192000,"salary_max":202500,"location":"Remote (US)","workplace":"remote","remote_scope":"restricted","job_type":"full-time","experience_level":"senior","tags":["embeddings","llm","agents","speech","search","generative-ai","rag","code-generation"],"apply_url":"https://instacart.careers/job/?gh_jid=8053797","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-09-02T21:03:54Z","expires_at":"2026-11-13T16:57:55.635503Z","created_at":"2026-09-03T13:40:00.251564Z","updated_at":"2026-10-14T16:57:55.638788Z","company_name":"Instacart","company_slug":"instacart","company_logo_url":"https://www.google.com/s2/favicons?domain=www.instacart.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/9a398fdb-238a-481a-bd92-943d478410ae"},{"id":"23b07459-84fa-4416-bbea-feb6fb2adeba","company_id":"19a78c6a-11dc-4d21-8273-0d2d2bad39b1","title":"Staff/Senior Software Engineer, Voice AI Platform","slug":"staff-software-engineer-voice-ai-platform-5d1785a9","description":"Location(s):  US (remote), Boston (hybrid), or New York (hybrid)\n  \n Who We Are \n Toast is driven by building the restaurant platform that helps restaurants adapt, take control, and get back to what they do best: building the businesses they love. We are looking for a Staff Software Engineer to join the Voice AI Team.\n On the Voice AI Team, our mission is to build and operate the voice platform that powers Toast and to ship novel applications on top of it that create real value across Toast's customer base. This is a greenfield space where the platform and its use cases are being defined together, and the work you do here will be foundational to how Toast uses voice AI for years to come.\n As a Software Engineer on this team, you'll take ownership of significant projects end-to-end: designing systems, driving execution across the team, and making the technical decisions that shape how the platform grows. You'll work closely with product, engineering, and stakeholders across Toast to turn ambiguous problems into reliable, scalable systems.\n About this roll* (Responsibilities) \n \n Design, build, deploy, and maintain highly resilient and scalable backend services, applications, and core platform components supporting Toast's Voice AI platform used across teams\n Conceive and lead complex, cross-cutting projects from design through production, owning outcomes and driving alignment across stakeholders and across a broad range of stakeholders\n Shape the technical direction on your team and beyond by making architectural decisions, defining patterns, and reducing complexity for the engineers and teams that depend on your work\n Build and evolve integrations with AI platforms and internal Toast systems, making pragmatic tradeoffs between speed, reliability, and long-term scalability\n Establish and implement patterns for observability, monitoring, and evaluation frameworks for AI-powered systems, using production data to understand and continuously improve system behavior\n Set and hold the bar for engineering quality and best practices through standards, patterns, and written guidance that others naturally adopt, raising the bar for the team and the broader organization\n Mentor engineers at all levels through code reviews, design feedback, and technical guidance \n \n Do you have the right ingredients*? (Requirements) \n \n 8+ years of experience with object-oriented languages such as Java or Kotlin \n Bachelor’s degree in Computer Science, Software Engineering, Computer Engineering, or related field\n Experience developing AI-integrated products or features , with a practical understanding of how to ship and iterate on systems that incorporate LLMs or other AI capabilities\n Experience building and reasoning about AI-powered systems , including nondeterminism, evaluation strategies, observability, and cost management\n Experience shipping complex, mission-critical production services and owning them long-term\n Track record of leading multi-person and multi-team projects end-to-end, from design through rollout\n Deep understanding of distributed systems, scalability, and production reliability\n Basic familiarity with frontend development\n Strong cross-team communication and collaboration skills; able to influence direction without formal authority both within your team and across the broader organization\n Actively uses AI coding tools (e.g., Claude Code, Cursor) in day-to-day development and have caused others to become more proficient with AI coding tools\n Experience with voice or conversational AI platforms is a plus, but not required\n \n Our Tech Stack \n Our backend services follow a microservice architecture written in Kotlin and Java using DropWizard, running on AWS (DynamoDB, RDS, Lambda). We store data in sharded Postgres databases and have our own platform for user management, canary deployments, and load balancing. Our web front-end is built with React and ES6.\n  \n AI at Toast \n At Toast, one of our company values is that we're hungry to build and learn. We believe learning new AI tools empowers us to build for our customers faster, more independently, and with higher quality. We provide these tools across all disciplines, from Engineering and Product to Sales and Support, and are inspired by how our Toasters are already driving real value with them. The people who thrive here are those who embrace changes that let us build more for our customers; it’s a core part of our culture.\n Our Total Rewards Philosophy  We strive to provide competitive compensation and benefits programs that help to attract, retain, and motivate the best and brightest people in our industry. Our total rewards package goes beyond great earnings potential and provides the means to a healthy lifestyle with the flexibility to meet Toasters’ changing needs. Learn more about our benefits at  https://careers.toasttab.com/toast-benefits .\n  \n  \n The base salary range for this role is listed below. The starting salary will be determined base","salary_min":151000,"salary_max":242000,"location":"Remote (US)","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["microservices","distributed-systems","cloud","speech","llm"],"apply_url":"https://careers.toasttab.com/jobs?gh_jid=8131117","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-17T03:54:54Z","expires_at":"2026-11-13T16:58:22.394371Z","created_at":"2026-08-25T18:29:28.909723Z","updated_at":"2026-10-14T16:58:22.397576Z","company_name":"Toast","company_slug":"toast","company_logo_url":"https://www.google.com/s2/favicons?domain=pos.toasttab.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/23b07459-84fa-4416-bbea-feb6fb2adeba"},{"id":"dc54d254-d290-4242-871b-1d784c72c570","company_id":"0fc88a91-688e-421d-917d-4880569dd976","title":"Principal Research \u0026 Engineering, Realtime Voice AI","slug":"principal-research-engineering-realtime-voice-ai-9c626749","description":"About Inflection AI \n Inflection AI is a Public Benefit Corporation empowering people with human-centered, emotionally intelligent AI. We’re shaping the future of AI by combining emotional intelligence (EQ) and raw intelligence (IQ) to elevate people’s potential. Inflection AI created Pi, the world’s first emotionally intelligent AI, to help people work through decisions, emotions, and challenges. Pi is a personal AI agent powered by Inflection AI’s foundation model, proving that AI can be personal, empathetic, and contextually aware.\n About the Role \n Voice is becoming the highest-stakes interface for AI, where quality depends on speed, naturalness, interruption handling, emotional nuance, and reliability in real-world conditions. We are looking for a hands-on technical leader to define and build Inflection’s realtime Voice AI stack across speech models, streaming systems, voice-agent runtime, and evaluation. This person will help shape how emotionally intelligent AI shows up in spoken interactions, partnering across research, engineering, product, and design to deliver voice agents that feel responsive, trustworthy, and useful in enterprise settings. \n What You’ll Do \n \n Establish the technical roadmap for Inflection's realtime Voice AI stack, encompassing streaming ASR, TTS, speech-to-speech, speech LLMs, turn-taking, barge-in, latency, and reliability.\n Utilize a 1,000 GPU cluster to support performance benchmarking and extensive experimentation.\n Determine build-vs-buy-vs-train strategies for core audio, speech, and realtime interaction components.\n Direct research and engineering efforts focused on speech quality, naturalness, expressiveness, emotional fit, controllability, and production readiness.\n Collaborate with infrastructure, product, design, and agentic AI teams to deploy voice agents for enterprise workflows.\n Develop evaluation systems measuring voice quality through metrics such as clarity, emotional appropriateness, interruption handling, task success, user preference, latency, and reliability, moving beyond standard WER.\n Refine production voice behavior by debugging across runtime, model, evaluation, data, and product layers.\n Mentor, and Coach a team specializing in speech research, audio infrastructure, realtime systems, and evaluation.\n \n What We’re Looking For \n \n Experience leading or serving as a principal Research and Engineering contributor to realtime voice, speech, audio AI, or conversational AI systems in production.\n Experience with one or more of: streaming ASR, TTS, speech-to-speech systems, speech LLMs, audio tokenization, multimodal models, barge-in, low-latency inference, or realtime agents.\n Strong technical judgment across both speech modeling and production systems.\n Ability to define voice quality in terms of user and customer outcomes, not only offline model metrics.\n Experience designing or using evaluation systems that capture real user experience.\n Strong product intuition for natural, trustworthy, emotionally appropriate voice interactions.\n Ability to lead senior technical talent while staying close to the code, architecture, and debugging work.\n Have a bachelor’s degree or equivalent in a related field to the offered position requirements\n \n Employee Pay Disclosures \n At Inflection AI, we aim to attract and retain the best employees and compensate them in a way that appropriately and fairly values their individual contributions to the company. For this role, Inflection AI estimates a starting annual base salary to fall within the range of $400,000 to $550,000 , depending on a candidate’s qualifications and level of experience. This role also includes a meaningful equity component, allowing employees to share in the long-term success of the company.\n  \n Benefits \n Inflection AI values and supports our team’s mental, emotional, financial and physical health. We are focused on building a positive, safe, inclusive and inspiring place to work. Our benefits include: \n \n Robust medical, dental and vision options with employer contributions for HSA, FSA and DFSA\n 401k matching program \n Flexible Time Off, 10 paid holidays, 5 days sick leave\n Parental, Medical and Family care leave \n Generous cell-phone, wellness and office set up stipends \n Support of country-specific visa needs for international employees living in the Bay Area","salary_min":400000,"salary_max":550000,"location":"Palo Alto, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"principal","tags":["gpu","generative-ai","llm","agents","speech","research"],"apply_url":"https://boards.greenhouse.io/inflectionai/jobs/4693024006?gh_jid=4693024006","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-06-29T18:24:22Z","expires_at":"2026-11-13T16:55:57.840016Z","created_at":"2026-06-30T14:04:31.512807Z","updated_at":"2026-10-14T16:55:57.842798Z","company_name":"Inflection AI","company_slug":"inflection-ai","company_logo_url":"https://www.google.com/s2/favicons?domain=inflection.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/dc54d254-d290-4242-871b-1d784c72c570"},{"id":"bc38cbd7-6147-49eb-a610-64fb031af669","company_id":"6ea0f41a-b13e-481a-b410-5195f391f939","title":"Staff Machine Learning Engineer, Voice AI ","slug":"staff-machine-learning-engineer-voice-ai-049973bf","description":"About the Role \n Together AI is building the best inference infrastructure for voice applications. Our Voice AI platform powers production-grade, real-time voice agents and applications — serving speech-to-text and text-to-speech models with best-in-class latency and reliability.\n We're looking for a Staff ML Engineer to drive the model serving layer for voice workloads. You'll work hands-on with inference engines like TRT-LLM and SGLang to optimize how we serve models like Whisper, Parakeet, Orpheus, and Kokoro — pushing latency and throughput to the frontier. You'll profile GPU utilization, design batching strategies for streaming audio, and ensure new model architectures can go from research to production quickly.\n This is a foundational hire on a small, high-impact team. Voice inference has unique challenges — streaming audio, tokenization, real-time latency budgets — that require dedicated ML engineering focus. You'll shape how Together serves voice models as the industry moves from pipeline architectures (ASR → LLM → TTS) toward end-to-end speech-to-speech.\n \n Own the model serving stack that powers Together's voice platform across STT, TTS, and speech-to-speech.\n Work directly with state-of-the-art accelerators (H100s, H200s, B200s) to optimize voice model inference.\n Collaborate with model partners (Cartesia, Deepgram, Rime, and others) to bring their models to production on Together's infrastructure.\n Build quality evaluation frameworks that guide model selection for customers and inform the roadmap.\n Join a small, early-stage team with outsized impact on a fast-growing product area.\n \n  \n Responsibilities \n \n Own the voice inference roadmap end-to-end — define and execute the technical strategy for optimizing STT, TTS, and speech-to-speech models across Together's infrastructure, with a clear-eyed view of where the field is heading and how to position the platform ahead of it.\n Drive best-in-class inference performance — architect and implement systems targeting leading TTFB, throughput, and GPU utilization for voice workloads; set the performance bar others in the industry measure against, not just catch up to.\n Lead productionization of voice models at scale — design the serving architecture for serverless and dedicated endpoints, including batching strategies, streaming inference pipelines, and memory management tailored to real-time audio; own reliability and latency SLAs.\n Build the voice evaluation platform — design a rigorous, extensible evaluation framework covering WER across accents, languages, and noise conditions for STT; naturalness, latency, and pronunciation fidelity for TTS; establish the internal benchmark methodology that informs model selection and roadmap decisions.\n Shape the architecture for next-generation model support — anticipate and enable emerging model paradigms — audio-native LLMs, codec-based architectures (SNAC, Encodec), and end-to-end speech-to-speech systems — before they're mainstream, not after.\n Serve as the technical DRI for model partner integrations — lead deep collaboration with partners such as Cartesia, Deepgram, and Rime; own the full lifecycle from integration to optimization to ongoing performance accountability.\n Diagnose and resolve the hardest performance problems in the stack — conduct systematic profiling and root-cause analysis from GPU kernel behavior to framework-level bottlenecks; drive shipped improvements with documented, measurable impact.\n Influence platform architecture across the organization — partner with platform engineering leadership to ensure the serving layer is built for the latency and reliability demands of real-time voice APIs; your technical decisions should raise the ceiling for the whole team.\n Define and scale voice fine-tuning capabilities — lead the technical direction for enabling customers to fine-tune STT and TTS models on Together's infrastructure, establishing the primitives for differentiated voice experiences.\n Lay technical foundations for a category-defining product surface — architect systems with enough foresight that they support multiple new voice products with minimal rework; think in terms of platforms, not point solutions.\n \n Requirements \n \n 8+ years of ML engineering experience, with a demonstrated focus on model serving, inference optimization, or ML infrastructure at production scale — including systems you've owned from design through live traffic.\n Deep, practical expertise in LLM serving engines (vLLM, SGLang, TensorRT-LLM, or equivalent) — you've modified engine internals, debugged edge cases under load, and contributed improvements back; you don't stop at the API surface.\n Expert-level Python and PyTorch proficiency, with a strong command of GPU optimization — CUDA kernels, memory hierarchies, profiling toolchains — and a track record of turning that knowledge into shipped latency or throughput wins.\n Proven system design judgment — you've made arch","salary_min":220000,"salary_max":280000,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["reinforcement-learning","llm","mlops","speech","gpu","pre-training","pytorch","fine-tuning"],"apply_url":"https://job-boards.greenhouse.io/togetherai/jobs/5140763007","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-19T18:19:46Z","expires_at":"2026-11-13T16:55:08.962926Z","created_at":"2026-05-27T14:02:00.695384Z","updated_at":"2026-10-14T16:55:08.965777Z","company_name":"Together AI","company_slug":"together-ai","company_logo_url":"https://www.google.com/s2/favicons?domain=together.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/bc38cbd7-6147-49eb-a610-64fb031af669"},{"id":"9d1d550a-8f83-478f-9177-feb5d26a9adc","company_id":"776e5e7d-beba-4889-a481-6d9d7c3af325","title":"Senior Research Engineer, Audio and Speech","slug":"senior-research-engineer-voice-speech-1d2a6c12","description":"About Decagon\n\nDecagon is the leading conversational AI platform empowering every brand to deliver concierge customer experiences.\n\nOur technology enables industry-defining enterprises like Avis Budget Group, Block’s Cash App and Square, Chime, Oura Health, and Hunter Douglas to deploy AI agents that power personalized, deeply satisfying interactions across voice, chat, email, SMS, and every other channel.\n\nWe’re building a future where customer experiences are being redefined from support tickets and hold music to faster resolutions, richer conversations, and deeper relationships. We’re proud to be backed by world-class investors who share that vision, including a16z, Accel, Bain Capital Ventures, Coatue, and Index Ventures, along with many others.\n\nWe’re an in-office company, driven by a shared commitment to excellence and velocity. Our values — Just Get It Done, Invent What Customers Want, Winner’s Mindset, and The Polymath Principle — shape how we work and grow as a team.\n\n\n\nAbout the Team\n\nRead more about the Speech Research Team's work:\n\n - https://decagon.ai/blog/audio-native-semantic-speaker-change-detection\n\n - https://decagon.ai/blog/scaling-real-time-tts-inference\n\n - https://decagon.ai/blog/teaching-flow-matching-tts-with-rl\n\nThe Research team develops the model and decision-making stack that powers Decagon’s conversational agents for enterprise support. We research, adapt, and implement state-of-the-art techniques in model training, prompting, orchestration, and evaluation in order to make our agents more accurate, robust, and efficient in real-world deployments.\n\nOur goal is to push the frontier of applied conversational AI: agents that reliably understand nuanced intent, track long context, and take the right actions under uncertainty. We measure success the way customers feel it: higher resolution rates, better user satisfaction, and consistent behavior at scale.\n\n\n\nAbout the Role\n\nAs a Research Engineer focused on Audio and Speech, you’ll be responsible for building the models and agent harnesses that power Decagon’s real-time voice agents and taking them all the way from idea to production. Your work will advance multimodal and full-duplex systems that can listen, reason, speak, and respond naturally in real time.\n\nWe’re looking for strong engineers who want to build the next generation of AI voice agents. People here own their work end-to-end, ship real improvements, and are trusted to make high-impact technical decisions.\n\n\n\nIn this role, you will\n\n - Design and build next-generation agent harnesses optimized for streaming speech, turn-taking, interruptions, overlapping speech, and continuous interaction\n\n - Research and train multimodal and full-duplex models that jointly understand audio, reason, and generate speech\n\n - Improve speech recognition, voice activity detection, endpointing, and speech generation across diverse speakers, environments, domains, and languages\n\n - Build evaluations and use production calls to ship measurable improvements in accuracy, latency, naturalness, and task outcomes\n\n - Optimize end-to-end inference for responsiveness, throughput, stability, and cost, partnering with Voice Platform and Infrastructure teams to deploy at scale\n\n\n\nYour background looks something like this\n\n - 4+ years of experience in speech, audio ML, multimodal ML, or production machine learning\n\n - Experience developing or adapting autoregressive, diffusion, flow-matching, or codec-based speech models\n\n - Hands-on experience with streaming agent systems, low-latency inference, production model serving, and evaluation on real-world audio\n\n - Fluency in Python and a modern deep-learning framework such as PyTorch, with strong foundations in machine learning and signal processing\n\n - A track record of taking research ideas from prototype to reliable, measurable production impact\n\n\nEven better if you have\n\n - Familiarity with speech-to-speech or full-duplex models\n\n - Experience with telephony, multilingual speech, noisy-channel robustness, speaker adaptation, or expressive speech generation\n\n\n\nCompensation\n\n$200K – $400K + Offers Equity\n\n\n\nBenefits\n\nWe proudly offer the following benefits for our full-time employees:\n\n - Medical, Dental, and Vision benefits for you and your family\n\n - Life Insurance and Disability Benefits\n\n - Retirement Plan (e.g., 401K, pension)\n\n - Parental Leave\n\n - Fertility and family building benefits through Carrot\n\n - Monthly stipend to support your wellness, lifestyle, and work-life balance\n\n - Daily lunches and snacks in the office to keep you at your best\n\n - Take what you need vacation policy (subject to local requirements; UK employees receive 25 days of statutory leave)\n\nThese benefits are described in more detail in Decagon’s policies, may vary by location, and can change at any time according to applicable compensation and benefits plans.","salary_min":200000,"salary_max":400000,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["mlops","pytorch","speech","agents","search","research"],"apply_url":"https://jobs.ashbyhq.com/decagon/4a69b01d-6388-462a-8336-7cb288a87a0e/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-05-18T17:36:47.593Z","expires_at":"2026-11-13T16:57:20.642619Z","created_at":"2026-05-27T14:07:26.70718Z","updated_at":"2026-10-14T16:57:20.64529Z","company_name":"Decagon","company_slug":"decagon","company_logo_url":"https://www.google.com/s2/favicons?domain=decagon.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/9d1d550a-8f83-478f-9177-feb5d26a9adc"},{"id":"e166cabe-5ba5-4fe5-a30d-688ddd5f8fc1","company_id":"5dfcd8fc-f8dd-4f46-b613-ca6da467ff4b","title":"Machine Learning Researcher, Audio","slug":"machine-learning-researcher-audio-6b0906fa","description":"MACHINE LEARNING RESEARCHER, AUDIO\n\nLocation: San Francisco, CA or Remote\n\n \n \n\n\nABOUT BLAND\n\nAt Bland.com, our mission is to empower enterprises to build AI phone agents at scale. Based in San Francisco, we are a fast-growing team reimagining how customers interact with businesses through voice. We have raised $100 million from leading Silicon Valley investors, including Emergence Capital, Scale Venture Partners, Y Combinator, and founders of Twilio, Affirm, and ElevenLabs.\n\n \n\nVoice is quickly becoming the primary interface between businesses and their customers. We are building the models and infrastructure that make those interactions feel natural, reliable, and genuinely human.\n\n \n \n\n\nTHE ROLE: MACHINE LEARNING RESEARCHER, AUDIO\n\nAs a Machine Learning Researcher at Bland, you'll be working on foundational research and development across the core components of our voice stack: speech-to-text, large language models, neural audio codecs, and text-to-speech. Your work will define how our agents understand, reason, and speak in real time at enterprise scale.\n\n \n\nThis is not a narrow research role. You will take ideas from theory to large-scale training to production inference systems serving millions of calls per day. You will design new modeling approaches, validate them with rigorous experimentation, and collaborate with engineering teams to deploy them into real customer environments.\n\n \n \n\n\nWHAT YOU WILL DO\n\nBuild and Scale Next-Generation TTS Systems\n\n - Design and train large scale text-to-speech models capable of expressive, controllable, human-sounding output.\n\n - Develop neural audio codec-based TTS architectures for efficient, high-fidelity generation.\n\n - Improve prosody modeling, question inflection, emotional expression, and multi-speaker robustness.\n\n - Optimize for real-time, low-latency inference in production.\n\n \n\nAdvance Speech-to-Text Modeling\n\n - Build and fine-tune large scale ASR systems robust to accents, noise, telephony artifacts, and code switching.\n\n - Leverage self-supervised pretraining and large-scale weak supervision.\n\n - Improve transcription accuracy for real-world enterprise scenarios, including structured extraction and conversational nuance.\n\n \n\nPioneer Neural Audio Codecs\n\n - Research and implement neural audio codecs that achieve extreme compression with minimal perceptual loss.\n\n - Explore discrete and continuous latent representations for scalable speech modeling.\n\n - Design codec architectures that enable downstream generative modeling and controllable synthesis.\n\n \n\nDevelop Scalable Training Pipelines\n\n - Curate and process massive audio datasets across languages, speakers, and environments.\n\n - Design staged training curricula and data filtering strategies.\n\n - Scale training across distributed GPU clusters focusing on cost, throughput, and reliability.\n\n \n\nRun Rigorous Experiments\n\n - Design ablation studies that isolate the impact of architectural changes.\n\n - Measure improvements using both objective metrics and perceptual evaluations.\n\n - Validate ideas quickly through focused experiments that confirm or eliminate hypotheses.\n\n \n \n\n\nWHAT MAKES YOU A GREAT FIT\n\nDeep Research Foundations\n\n - Experience with self-supervised learning, multimodal modeling, or generative modeling.\n\n - Ability to derive new formulations and implement them efficiently.\n\n \n\nExpertise in Voice Modeling\n\n - Hands-on experience building or scaling TTS, STT, or neural audio codec systems.\n\n - Familiarity with large scale speech datasets and real-world audio variability.\n\n - Strong intuition for audio quality, prosody, and conversational dynamics.\n\n \n\nSystems and Hardware Awareness\n\n - Experience training and serving large models on modern accelerators.\n\n - Knowledge of inference optimization techniques, including quantization, kernel optimization, and memory efficiency.\n\n - Understanding of real-time constraints in telephony or streaming environments.\n\n \n\nExperimental Rigor\n\n - Track record of designing controlled experiments and meaningful ablations.\n\n - Comfortable working with both offline benchmarks and live production metrics.\n\n - Ability to move quickly from hypothesis to validation.\n\n \n\nBuilder Mentality\n\n - Comfortable in fast-moving startup environments.\n\n - Strong ownership mindset from research through deployment.\n\n - Excited by ambiguous, unsolved problems.\n\n \n \n\n\nHOW YOU SHOW UP\n\n - You treat unsolved problems as opportunities to invent new paradigms.\n\n - You identify the single experiment that can validate an idea in days, not months.\n\n - You measure everything and let data drive decisions.\n\n - You are obsessed with making voice agents sound truly human.\n\n - You use AI tools aggressively to amplify your own impact and accelerate research cycles.\n\n \n \n\n\nBONUS POINTS\n\n - Experience with large scale distributed training.\n\n - Research publications or open source contributions in speech or language AI.\n\n - Background in real-time speech systems or telephony.\n\n","salary_min":160000,"salary_max":280000,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["pre-training","healthcare","gpu","speech","llm","distributed-systems","machine-learning","research"],"apply_url":"https://jobs.ashbyhq.com/bland/2e815d0d-8e7a-43cc-8853-c1b029aeb499/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-04-20T22:07:11.702Z","expires_at":"2026-11-13T16:56:52.327018Z","created_at":"2026-04-22T15:40:14.708917Z","updated_at":"2026-10-14T16:56:52.330293Z","company_name":"Bland AI","company_slug":"bland-ai","company_logo_url":"https://www.google.com/s2/favicons?domain=bland.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/e166cabe-5ba5-4fe5-a30d-688ddd5f8fc1"},{"id":"fdeb7783-851b-48d1-810b-3d39970161b6","company_id":"6ea0f41a-b13e-481a-b410-5195f391f939","title":"Senior Machine Learning Engineer, Voice AI ","slug":"senior-machine-learning-engineer-voice-ai-e60e860b","description":"About the Role \n Together AI is building the best inference infrastructure for voice applications. Our Voice AI platform powers production-grade, real-time voice agents and applications — serving speech-to-text and text-to-speech models with best-in-class latency and reliability.\n We're looking for a Senior ML Engineer to drive the model serving layer for voice workloads. You'll work hands-on with inference engines like TRT-LLM and SGLang to optimize how we serve models like Whisper, Parakeet, Orpheus, and Kokoro — pushing latency and throughput to the frontier. You'll profile GPU utilization, design batching strategies for streaming audio, and ensure new model architectures can go from research to production quickly.\n This is a foundational hire on a small, high-impact team. Voice inference has unique challenges — streaming audio, tokenization, real-time latency budgets — that require dedicated ML engineering focus. You'll shape how Together serves voice models as the industry moves from pipeline architectures (ASR → LLM → TTS) toward end-to-end speech-to-speech.\n \n Own the model serving stack that powers Together's voice platform across STT, TTS, and speech-to-speech.\n Work directly with state-of-the-art accelerators (H100s, H200s, B200s) to optimize voice model inference.\n Collaborate with model partners (Cartesia, Deepgram, Rime, and others) to bring their models to production on Together's infrastructure.\n Build quality evaluation frameworks that guide model selection for customers and inform the roadmap.\n Join a small, early-stage team with outsized impact on a fast-growing product area.\n \n Responsibilities \n \n Optimize inference performance for voice models (STT, TTS, speech-to-speech) — targeting best-in-class TTFB, throughput, and GPU utilization across our curated model set.\n Productionize voice models on serverless and dedicated endpoints, including batching strategies, streaming inference, and memory management tailored to audio workloads.\n Build and maintain a voice model evaluation framework — measuring WER across accents, languages, and noise conditions for STT; naturalness, latency, and pronunciation accuracy for TTS.\n Enable new model architectures in our serving stack as the field evolves, including audio-native LLMs, codec-based models (SNAC), and speech-to-speech systems.\n Collaborate with model partners to integrate and optimize their models (Cartesia, Deepgram, Rime, and others) running on Together's infrastructure.\n Profile and debug performance across the full inference stack — from GPU kernels to framework-level bottlenecks — and ship measurable improvements.\n Work with the platform engineering side of the team to ensure the serving layer meets the latency and reliability requirements of real-time voice APIs.\n Contribute to voice model fine-tuning capabilities (STT and TTS) as we enable customers to build differentiated voice experiences on Together.\n Lay the groundwork for multiple new products down the line.\n \n Requirements \n \n 5+ years of experience in ML engineering, with a focus on model serving, inference optimization, or ML infrastructure.\n Hands-on experience with LLM serving engines (vLLM, SGLang, TensorRT-LLM, or similar) — comfortable reading and modifying engine internals, not just using APIs.\n Strong proficiency in Python and PyTorch; experience with GPU profiling and optimization (CUDA, memory management, kernel-level debugging).\n Track record of shipping ML systems to production with measurable performance improvements.\n Strong product sense — you think about what developers building voice apps actually need, not just what's technically interesting.\n Comfort working on a small, early-stage team where you'll wear multiple hats and move fast.\n Experience with speech and audio ML (ASR, TTS architectures, audio signal processing) is a strong plus but not required — you can learn this quickly if you have strong ML engineering fundamentals.\n Familiarity with audio codecs and tokenization schemes (SNAC, Encodec, DAC) is a plus.\n Experience training or fine-tuning speech models is a plus.\n Bachelor's or Master's degree in Computer Science, Electrical Engineering, or related field, or equivalent practical experience\n \n About Together AI \n Together AI, the AI Native Cloud, is purpose-built for AI engineers. AI application developers get high-performance inference that scales reliably, fine-tuning and reinforcement learning for creating frontier-level specialized models, and pre-training at massive scale for fully custom intelligence, all around a marketplace of leading open models that teams can run, adapt, and own. Trusted by Cursor, Decagon, ElevenLabs, Salesforce, and Zoom, Together serves 400+ trillion tokens a month.\n Compensation \n We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $200,000 - $260,000 + equity + benefits. Our salary ranges ar","salary_min":200000,"salary_max":260000,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["mlops","pre-training","reinforcement-learning","pytorch","speech","fine-tuning","gpu","llm"],"apply_url":"https://job-boards.greenhouse.io/togetherai/jobs/5088817007","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-03-30T19:36:00Z","expires_at":"2026-11-13T16:55:08.894572Z","created_at":"2026-04-13T09:37:38.250213Z","updated_at":"2026-10-14T16:55:08.89733Z","company_name":"Together AI","company_slug":"together-ai","company_logo_url":"https://www.google.com/s2/favicons?domain=together.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/fdeb7783-851b-48d1-810b-3d39970161b6"},{"id":"6bdbfae6-b541-4956-99e1-7b2487292755","company_id":"7551b4ca-b2b0-493a-ab58-a15bd9c50393","title":"Lead Engineer - AI Agent Voice Experience ","slug":"senior-machine-learning-engineer-automatic-speech-recognition-asr-31bbe25d","description":"Cresta unlocks the true potential of the customer experience, turning every conversation into a competitive advantage. Cresta’s unified AI platform combines conversational AI agents, real-time human agent augmentation, and comprehensive conversation intelligence to drive revenue and efficiency gains across every channel. The world’s leading companies, including United Airlines, Cox Communications, and Marriott, use Cresta to power world-class customer experiences every day. \n Born from the Stanford AI Lab, Cresta has raised more than $270 million from the world’s leading investors, including a16z, Greylock, and Sequoia. Cresta’s leadership includes some of the leading minds in AI today. Our CEO, Ping Wu , founded and led Google's Contact Center AI and Vertex AI platforms before joining Cresta to build the future of AI-driven customer experiences.\n Over the next few years, AI is going to redefine how people all over the world interact with businesses every day. Come build that future at Cresta.\n About the role \n We are looking for a Lead Engineer, AI Agent Voice Experience to help build the next generation of AI-powered voice systems for the contact center. In this role, you will work at the intersection of speech, language, and real-time production systems, improving how AI listens, understands, reasons, empathizes, and responds in live customer conversations. \n You will develop and improve machine learning systems that power voice experiences end to end, including automatic speech recognition, turn detection, agentic workflows, voice evaluation, text to speech, speech-to-speech models, and production optimization. You will partner closely with applied researchers, product managers, designers, forward deployed engineers, and platform engineers to ensure model and system improvements translate into measurable customer and business impact.\n This role is ideal for someone who is excited by both model quality and production reality: designing rigorous evaluation frameworks, analyzing failure modes, improving latency and robustness, elevating caller interaction experience, and shipping systems that perform reliably at scale in real-time voice environments.\n Responsibilities \n \n Design, train, evaluate, and deploy machine learning systems that power real-time voice experiences, including speech to text turn detection, text to speech, speech to speech, reasoning and structured insight generation.\n Improve the quality of voice AI systems through error analysis, data curation, metric design, benchmarking, and iterative model improvement, with a strong focus on real-world performance.\n Build evaluation frameworks for complex voice and agentic systems, measuring metrics such as accuracy, robustness, latency, faithfulness, naturalness, professionalism, task completion, and cost.\n Diagnose and mitigate failure modes across the voice stack, including transcription errors, hallucinations, tool misuse, prompt brittleness, context drift, and multi-step reasoning breakdowns.\n Design, implement,  and optimize low-latency ML systems that deliver delightful caller experience (e.g., backchanneling, focusing on foreground speaker, interpreting caller’s emotions, responding with empathy).\n Partner with platform and backend engineers to productionize real-time inference, streaming pipelines, quality monitoring, and continuous model iteration.\n Collaborate cross-functionally with product, design, frontend, and backend teams to integrate voice intelligence seamlessly into Cresta’s platform.\n Mentor engineers, contribute to technical strategy, and help shape the roadmap for Cresta’s voice AI systems.\n \n Qualifications we value \n \n Bachelor’s degree in Computer Science, Mathematics, Machine Learning, AI, or a related field; Master’s or Ph.D. preferred.\n 5+ years of experience building, evaluating, and deploying machine learning systems in production.\n Demonstrated experience in leading fast-moving, highly technical teams. Strong communication skills, with the ability to influence cross-functional decisions and raise the engineering bar.\n Distinctive technical vision for the future of voice AI.\n Strong background in one or more of the following: speech recognition, speech processing, NLP, generative AI, or voice AI.\n Deep experience with model evaluation, benchmarking, error analysis, and quality improvement for production ML systems.\n Solid understanding of transformer-based models, embeddings, retrieval systems, and large-scale training or inference workflows.\n Experience designing and deploying real-time ML systems with strong requirements around latency, scalability, and reliability.\n Experience building data pipelines and tooling for experimentation, measurement, and large-scale quality analysis.\n Ability to work across research and engineering boundaries and translate promising ideas into production-grade systems.\n \n Nice to have \n \n Hands-on experience with ASR quality metrics such as WER and task-level evalu","salary_min":205000,"salary_max":270000,"location":"United States","workplace":"remote","remote_scope":"restricted","job_type":"full-time","experience_level":"lead","tags":["generative-ai","speech","data-pipeline","agents","llm","rag","nlp"],"apply_url":"https://job-boards.greenhouse.io/cresta/jobs/5155675008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-03-17T14:31:23Z","expires_at":"2026-11-13T16:55:47.883898Z","created_at":"2026-04-13T09:39:51.929183Z","updated_at":"2026-10-14T16:55:47.887015Z","company_name":"Cresta","company_slug":"cresta","company_logo_url":"https://www.google.com/s2/favicons?domain=cresta.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/6bdbfae6-b541-4956-99e1-7b2487292755"},{"id":"9b14ccd0-d998-4a7e-9345-48947ff5c9c2","company_id":"4d985fa4-b897-4f93-9745-c332367ad86b","title":"Senior Billing Manager","slug":"senior-billing-manager-2c044fa9","description":"ABOUT RETELL AI\n\nRetell AI is using first-principles thinking to reimagine the call center with cutting-edge voice AI. Thousands of companies now use Retell's AI voice agents to handle sales, support, and logistics calls that once required large teams of human agents. Backed by Y Combinator, Alt Capital, and other leading investors, we've scaled to $80M in ARR with a team of 50, up from $5M at the start of 2025, and are now valued at over $1.5B.\n\nOur vision for 2026 is to build a modern CX platform where entire contact centers are powered by AI. Instead of basic automation that needs constant human tuning, we're creating intelligent AI “workers” that act as frontline agents, QA analysts, and managers, continuously executing, monitoring, and improving every customer interaction.\n\nWe're growing fast and looking for ambitious builders who want to tackle hard technical problems, move quickly, and have a real impact on one of the fastest-growing voice AI companies in the world.\n\nLet's build the future together.\n\nRecent recognition:\n\n - No. 1 Best Places to Work in the Bay Area, San Francisco Business Times 2026 https://finance.yahoo.com/technology/ai/articles/voice-ai-startup-retell-ai-145200025.html\n\n - Top 50 AI Apps, a16z (2025) https://a16z.com/the-ai-application-spending-report-where-startup-dollars-really-go/\n\n - #3 Fastest-Growing Software Company, G2 Best Software Awards 2026 https://company.g2.com/news/g2s-2026-best-software-awards\n\n - Best Agentic AI Software, G2 Best Software Awards 2026 https://www.retellai.com/blog/retell-ai-recognized-as-the-best-agentic-ai-software-by-g2\n\n - #4 Fastest-Growing Software Vendor, Brex Benchmark 2025 https://www.brex.com/journal/brex-benchmark-december-2025\n\n - Enterprise Tech 30 Class of 2026, Nasdaq \u0026 Wing VC https://www.nasdaq.com/videos/retell-ai\n\n - Top-Ranked Startup, Lean AI Leaderboard https://leanaileaderboard.com/\n\n - Backed by Y Combinator https://www.ycombinator.com/companies/retell-ai\n\n \n\n\nABOUT THE ROLE\n\nRetell AI transforms customer experience with voice AI for enterprises, including customers like CVS/Aetna, American Airlines, Lenovo, and Grab. We have more customer stories than we can tell!\n\nWe're hiring our first billing owner. Revenue has grown from $5M to $80M ARR in under two years, with enterprise and usage-based contracts now flowing through the business. You'll build billing, AR from scratch: the processes, systems, and controls, and eventually the team.\n\n\n\n\nKEY RESPONSIBILITY\n\nThis hire owns enterprise accounts receivable, built from zero to one: invoices out on time, cash in predictably.\n\n - Build the enterprise AR process from scratch: invoicing, collections cadence, and cash application.\n\n - Own collections for enterprise accounts: aging, DSO, and disputes.\n\n - Set up invoicing for large contracts, including committed-spend and usage-based terms.\n\n - Work with Sales, Customer Success, and customers' AP teams on escalations.\n\n - Choose and set up the AR and billing tools; automate what you can.\n\n - Guide the contract accountants and report on AR health.\n\n\n\n\nWHAT WE'RE LOOKING FOR\n\nMust have:\n\n - 6+ years in AR, billing, or collections, including enterprise B2B.\n\n - Has built an AR or collections process from scratch at a high-growth SaaS or usage-based company.\n\n - Hands-on with billing and finance tools (e.g., Stripe, NetSuite, QuickBooks).\n\n - Confident working with large customers' AP and procurement teams.\n\n - Solid accounting fundamentals: AR aging, cash application, reconciliations.\n\nNice to have:\n\n - Experience with usage-based or committed-spend contracts.\n\n - CPA or audit experience.\n\n - First finance ops hire at a startup.\n\n\n\n\nHOW WE EVALUATE\n\nWe care less about checkboxes and more about:\n\n - Zero-to-one building: how you set up AR where none existed.\n\n - Collections results: lower DSO and fewer aged balances.\n\n - Judgment with large enterprise customers in invoice disputes.\n\n - Ownership under ambiguity.\n\n\n\n\nYOU MIGHT THRIVE IF\n\n - You'd rather ship a v1 in a week than plan for a month.\n\n - You're equally at home in a spreadsheet and on a call with a customer's AP team.\n\n - You want to set the foundation for how we get paid.\n\n \n\n\nJOB DETAILS\n\nCash: $190,000 - $230,000\n\nEquity: 4-year vest / 1-year cliff\n\nLocation: Redwood City, California (Relocation support provided)\n\nUS Visas: Retell AI is open to sponsoring work authorization for qualified candidates, including H-1B, TN, L-1, E-3, and F-1 (OPT/CPT).\n\n \n\n\nOTHER BENEFITS\n\n - 100% coverage for medical, dental, and vision insurance\n\n - $70/day DoorDash credit for breakfast, lunch, dinner, and snacks\n\n - $200/month wellness reimbursement (gym, fitness classes, etc.)\n\n - $300/month commuter reimbursement (gas, Caltrain, etc.)\n\n - $75/month phone bill reimbursement\n\n - $50/month internet reimbursement\n\n \n\n\nCOMPENSATION PHILOSOPHY\n\n - Best offer upfront: Choose from three cash-equity balance options; no negotiation needed\n\n - Top 1% talent: Above-market pay (top 5th percentile)","salary_min":190000,"salary_max":230000,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["payments","speech","agents"],"apply_url":"https://jobs.ashbyhq.com/retell-ai/98f1dd85-1967-418f-97f1-0439870d1e4e/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-14T06:37:59.771Z","expires_at":"2026-11-13T16:59:08.672699Z","created_at":"2026-10-14T15:22:40.460569Z","updated_at":"2026-10-14T16:59:08.675464Z","company_name":"Retell AI","company_slug":"retell-ai","company_logo_url":"https://www.google.com/s2/favicons?domain=retellai.com\u0026sz=128","quality_score":85,"url":"https://aidevboard.com/job/9b14ccd0-d998-4a7e-9345-48947ff5c9c2"},{"id":"39a84e3f-f578-4c9b-9d75-97bff8eaac42","company_id":"4d985fa4-b897-4f93-9745-c332367ad86b","title":"Senior IT Manager","slug":"senior-it-manager-bbf2845a","description":"ABOUT RETELL AI\n\nRetell AI is using first-principles thinking to reimagine the call center with cutting-edge voice AI. Thousands of companies now use Retell's AI voice agents to handle sales, support, and logistics calls that once required large teams of human agents. Backed by Y Combinator, Alt Capital, and other leading investors, we've scaled to $80M in ARR with a team of 50, up from $5M at the start of 2025, and are now valued at over $1.5B.\n\nOur vision for 2026 is to build a modern CX platform where entire contact centers are powered by AI. Instead of basic automation that needs constant human tuning, we're creating intelligent AI “workers” that act as frontline agents, QA analysts, and managers, continuously executing, monitoring, and improving every customer interaction.\n\nWe're growing fast and looking for ambitious builders who want to tackle hard technical problems, move quickly, and have a real impact on one of the fastest-growing voice AI companies in the world.\n\nLet's build the future together.\n\nRecent recognition:\n\n - No. 1 Best Places to Work in the Bay Area, San Francisco Business Times 2026 https://finance.yahoo.com/technology/ai/articles/voice-ai-startup-retell-ai-145200025.html\n\n - Top 50 AI Apps, a16z (2025) https://a16z.com/the-ai-application-spending-report-where-startup-dollars-really-go/\n\n - #3 Fastest-Growing Software Company, G2 Best Software Awards 2026 https://company.g2.com/news/g2s-2026-best-software-awards\n\n - Best Agentic AI Software, G2 Best Software Awards 2026 https://www.retellai.com/blog/retell-ai-recognized-as-the-best-agentic-ai-software-by-g2\n\n - #4 Fastest-Growing Software Vendor, Brex Benchmark 2025 https://www.brex.com/journal/brex-benchmark-december-2025\n\n - Enterprise Tech 30 Class of 2026, Nasdaq \u0026 Wing VC https://www.nasdaq.com/videos/retell-ai\n\n - Top-Ranked Startup, Lean AI Leaderboard https://leanaileaderboard.com/\n\n - Backed by Y Combinator https://www.ycombinator.com/companies/retell-ai\n\n \n\n\nABOUT THE ROLE\n\nRetell AI transforms customer experience with voice AI for enterprises, including customers like CVS/Aetna, American Airlines, Lenovo, and Grab. We have more customer stories than we can tell!\n\nWe're looking for a Senior IT Manager to help build and scale our internal IT operations.\n\nYou'll own day-to-day IT support while improving security, onboarding, hardware management, SaaS administration, and internal automation.\n\nThis is a highly hands-on role working directly with employees across Engineering, GTM, Product, and Operations. You'll be responsible for making sure every employee has the tools, access, and support they need to move quickly.\n\nThis is our first IT internal hire with the opportunity to make a meaningful impact on one of the fastest-growing AI companies.\n\n\n\n\nKEY RESPONSIBILITIES\n\n\nIT SUPPORT\n\n - Own employee onboarding and offboarding.\n\n - Configure laptops and workstations.\n\n - Troubleshoot hardware and software issues.\n\n - Manage Google Workspace, Slack, Rippling, SSO, and MDM platforms.\n\n - Support office networking, conference rooms, printers, and internal technology.\n\n\nSECURITY \u0026 COMPLIANCE\n\n - Maintain endpoint compliance.\n\n - Manage device inventory.\n\n - Support SOC2 compliance initiatives.\n\n - Conduct access reviews and security audits.\n\n - Help improve internal security practices.\n\n\nINTERNAL OPERATIONS\n\n - Manage hardware inventory.\n\n - Improve IT documentation.\n\n - Support office operations and employee productivity.\n\n - Partner with People Operations on onboarding and offboarding.\n\n\nAUTOMATION\n\n - Build automations around onboarding, SaaS provisioning, hardware lifecycle management, and internal IT workflows.\n\n - Continuously improve internal tooling and eliminate manual processes.\n\n\n\n\nWHAT WE'RE LOOKING FOR\n\nMust Have\n\n - Bachelor's degree in Computer Science, Information Systems, Computer Engineering, or a related field.\n\n - 2+ years of IT support or systems administration experience.\n\n - Experience administering macOS devices.\n\n - Experience with Google Workspace, MDM platforms, and identity management.\n\n - Strong troubleshooting and communication skills.\n\nNice to Have\n\n - Startup experience.\n\n - Experience with Rippling.\n\n - Python or Bash scripting.\n\n - Automation experience.\n\n - SOC2 compliance.\n\n - Jamf, Kandji, or Intune administration.\n\n\n\n\nYOU MIGHT THRIVE IF\n\n - You enjoy helping people solve technical problems.\n\n - You automate repetitive work whenever possible.\n\n - You like building systems instead of constantly fixing the same issues.\n\n - You move quickly and enjoy startup environments.\n\n - You enjoy improving processes and making teams more productive.\n\n - You take ownership and don't wait to be asked.\n\n \n\n\nJOB DETAILS\n\nCash: $200,000 - $250,000\n\nEquity: 4-year vest / 1-year cliff\n\nLocation: Redwood City, California (Relocation support provided)\n\nUS Visas: Retell AI is open to sponsoring work authorization for qualified candidates, including H-1B, TN, L-1, E-3, and F-1 (OPT/CPT).\n\n \n\n\nOTHER BENEFITS\n\n - 100","salary_min":200000,"salary_max":250000,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["agents","speech"],"apply_url":"https://jobs.ashbyhq.com/retell-ai/d54e194f-81ac-4c78-bbfc-f81dfc786bee/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-10-12T04:36:02.493Z","expires_at":"2026-11-13T16:59:08.735653Z","created_at":"2026-10-14T15:22:40.518529Z","updated_at":"2026-10-14T16:59:08.738818Z","company_name":"Retell AI","company_slug":"retell-ai","company_logo_url":"https://www.google.com/s2/favicons?domain=retellai.com\u0026sz=128","quality_score":85,"url":"https://aidevboard.com/job/39a84e3f-f578-4c9b-9d75-97bff8eaac42"},{"id":"5af94b53-8b43-4d4d-a83d-8d6fe455f44a","company_id":"776e5e7d-beba-4889-a481-6d9d7c3af325","title":"Agent UX Designer","slug":"agent-ux-designer-f37f905c","description":"About Decagon\n\nDecagon is the leading conversational AI platform empowering every brand to deliver concierge customer experiences.\n\nOur technology enables industry-defining enterprises like Avis Budget Group, Block’s Cash App and Square, Chime, Oura Health, and Hunter Douglas to deploy AI agents that power personalized, deeply satisfying interactions across voice, chat, email, SMS, and every other channel.\n\nWe’re building a future where customer experiences are being redefined from support tickets and hold music to faster resolutions, richer conversations, and deeper relationships. We’re proud to be backed by world-class investors who share that vision, including a16z, Accel, Bain Capital Ventures, Coatue, and Index Ventures, along with many others.\n\nWe’re an in-office company, driven by a shared commitment to excellence and velocity. Our values — Just Get It Done, Invent What Customers Want, Winner’s Mindset, and The Polymath Principle — shape how we work and grow as a team.\n\n\n\nAbout the Team\n\nOver the past few years, development of LLMs has evolved at a rapid pace. It’s not enough for our customers to just “set it and forget it” when it comes to AI software. Truly successful AI Agents require guidance and input throughout the development lifecycle.\n\n \n\nAbout the Role\n\nAs part of the Agent Experience Design team, you'll help shape what great AI conversation experiences look and sound like — across channels and languages, for enterprise customers around the world. You'll work directly with customers and internal teams to improve agent quality — especially in voice, one of our fastest growing channels — and build the systems and resources that allow us to scale your expertise.\n\nThis work spans research, design, enablement, and product strategy. You might:\n\n - Advise customers and internal teams on conversation design and voice selection\n\n - Evaluate and iterate on voice quality across providers, languages, and use cases\n\n - Build playbooks, rubrics, and evaluation frameworks that scale best practices across the team\n\n - Partner with Engineering and Product to translate field insights into platform improvements\n\nYour insights will shape how Decagon deploys AI in mission-critical contexts and how we build toward the next generation of intelligent systems.\n\n \n\nIn this role, you will\n\n - Design and optimize enterprise-grade AI conversation experiences across chat, voice, SMS, and email channels\n\n - Serve as a trusted advisor to customers and internal stakeholders on conversation design best practices\n\n - Evaluate voice quality and interaction patterns to maintain a high bar for naturalness and appropriateness\n\n - Build repeatable frameworks for assessing conversation and voice performance\n\n - Enable our Customer team to apply strong design judgment independently\n\n - Partner crossfunctionally with Engineering and Product to investigate quality gaps and drive improvements through clear recommendations\n\n - Share learnings and create documentation on best practices to improve consistency and raise the quality bar across deployments\n\n\n\nYour background looks something like this\n\n - 3-5+ years of relevant experience (e.g., voice experience design, conversation designer, product manager, applied linguistics, etc.)\n\n - Experience building evaluation frameworks, rubrics, or QA processes\n\n - Strong communicator across technical and business contexts\n\n - Comfortable working close to the product in a fast-moving environment\n\n \n\nEven better if you have\n\n - Native or professional fluency in Spanish and/or familiarity with other languages\n\n - Experience with TTS providers or speech synthesis tools\n\n - Hands-on experience with frontier AI tools and deployment in enterprise or high-impact settings\n\n\n\nCompensation\n\n$180K - $220K + Offers Equity\n\n \n\n\n\nBenefits\n\nWe proudly offer the following benefits for our full-time employees:\n\n - Medical, Dental, and Vision benefits for you and your family\n\n - Life Insurance and Disability Benefits\n\n - Retirement Plan (e.g., 401K, pension)\n\n - Parental Leave\n\n - Fertility and family building benefits through Carrot\n\n - Monthly stipend to support your wellness, lifestyle, and work-life balance\n\n - Daily lunches and snacks in the office to keep you at your best\n\n - Take what you need vacation policy (subject to local requirements; UK employees receive 25 days of statutory leave)\n\nThese benefits are described in more detail in Decagon’s policies, may vary by location, and can change at any time according to applicable compensation and benefits plans.","salary_min":180000,"salary_max":220000,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["speech","llm","agents"],"apply_url":"https://jobs.ashbyhq.com/decagon/56ca2731-eb4b-44cc-9f3f-c677a6ccb9df/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-09-30T17:01:27.26Z","expires_at":"2026-11-13T16:57:20.756255Z","created_at":"2026-10-14T15:21:05.928975Z","updated_at":"2026-10-14T16:57:20.759479Z","company_name":"Decagon","company_slug":"decagon","company_logo_url":"https://www.google.com/s2/favicons?domain=decagon.ai\u0026sz=128","quality_score":85,"url":"https://aidevboard.com/job/5af94b53-8b43-4d4d-a83d-8d6fe455f44a"},{"id":"48455c32-8097-4c20-8ecd-c6e4827ca374","company_id":"4d985fa4-b897-4f93-9745-c332367ad86b","title":"Senior Compliance Manager","slug":"senior-compliance-manager-ccc47c11","description":"ABOUT RETELL AI\n\nRetell AI is using first-principles thinking to reimagine the call center with cutting-edge voice AI. Thousands of companies now use Retell's AI voice agents to handle sales, support, and logistics calls that once required large teams of human agents. Backed by Y Combinator, Alt Capital, and other leading investors, we've scaled to $80M in ARR with a team of 50, up from $5M at the start of 2025, and are now valued at over $1.5B.\n\nOur vision for 2026 is to build a modern CX platform where entire contact centers are powered by AI. Instead of basic automation that needs constant human tuning, we're creating intelligent AI “workers” that act as frontline agents, QA analysts, and managers, continuously executing, monitoring, and improving every customer interaction.\n\nWe're growing fast and looking for ambitious builders who want to tackle hard technical problems, move quickly, and have a real impact on one of the fastest-growing voice AI companies in the world.\n\nLet's build the future together.\n\nRecent recognition:\n\n - No. 1 Best Places to Work in the Bay Area, San Francisco Business Times 2026 https://finance.yahoo.com/technology/ai/articles/voice-ai-startup-retell-ai-145200025.html\n\n - Top 50 AI Apps, a16z (2025) https://a16z.com/the-ai-application-spending-report-where-startup-dollars-really-go/\n\n - #3 Fastest-Growing Software Company, G2 Best Software Awards 2026 https://company.g2.com/news/g2s-2026-best-software-awards\n\n - Best Agentic AI Software, G2 Best Software Awards 2026 https://www.retellai.com/blog/retell-ai-recognized-as-the-best-agentic-ai-software-by-g2\n\n - #4 Fastest-Growing Software Vendor, Brex Benchmark 2025 https://www.brex.com/journal/brex-benchmark-december-2025\n\n - Enterprise Tech 30 Class of 2026, Nasdaq \u0026 Wing VC https://www.nasdaq.com/videos/retell-ai\n\n - Top-Ranked Startup, Lean AI Leaderboard https://leanaileaderboard.com/\n\n - Backed by Y Combinator https://www.ycombinator.com/companies/retell-ai\n\n \n\n\nABOUT THE ROLE\n\nRetell AI transforms customer experience with voice AI for enterprises, including customers like CVS/Aetna, American Airlines, Lenovo, and Grab. We have more customer stories than we can tell!\n\nWe're hiring our first Senior Compliance Manager to own Retell's security and compliance program end to end. You'll report directly to the founder and work closely with Engineering and Sales. Compliance unlocks our enterprise and healthcare deals, so your work has a direct line to revenue.\n\n\n\n\nKEY RESPONSIBILITY\n\nThis hire owns an audit-ready compliance program that enterprise customers trust.\n\n - Run SOC 2 Type II, HIPAA, and ISO 27001 programs end to end, including auditors and the GRC platform\n\n - Answer security questionnaires and RFPs quickly and keep the trust center current\n\n - Own policies, vendor risk, and training, and track new rules that affect voice AI\n\n - Join enterprise sales calls to answer security and compliance questions\n\n\n\n\nWHAT WE'RE LOOKING FOR\n\nMust have:\n\n - 4+ years in compliance, GRC, or security audit\n\n - You have personally owned at least one SOC 2 Type II audit\n\n - Experience at a VC-backed SaaS/AI company or a Big 4/audit firm doing SOC 2 or ISO work\n\nNice to have:\n\n - CISA, CISM, or CRISC certification\n\n - Hands-on with Vanta or Drata\n\n - HIPAA experience with healthcare customers\n\n\n\n\nHOW WE EVALUATE\n\nWe care less about checkboxes and more about:\n\n - Precision in controls, evidence, and documentation\n\n - Clear answers to customer security teams\n\n - Working with engineers without slowing them down\n\n - Spotting risks before an auditor or customer does\n\n\n\n\nYOU MIGHT THRIVE IF\n\n - You'd rather fix a gap early than explain it to an auditor\n\n - You can explain control to both an engineer and a CISO\n\n - You want to build a compliance program, not maintain one\n\n \n\n\nJOB DETAILS\n\nCash: $200,000 - $260,000\n\nEquity: 4-year vest / 1-year cliff\n\nLocation: Redwood City, California (Relocation support provided)\n\nUS Visas: Retell AI is open to sponsoring work authorization for qualified candidates, including H-1B, TN, L-1, E-3, and F-1 (OPT/CPT).\n\n \n\n\nOTHER BENEFITS\n\n - 100% coverage for medical, dental, and vision insurance\n\n - $70/day DoorDash credit for breakfast, lunch, dinner, and snacks\n\n - $200/month wellness reimbursement (gym, fitness classes, etc.)\n\n - $300/month commuter reimbursement (gas, Caltrain, etc.)\n\n - $75/month phone bill reimbursement\n\n - $50/month internet reimbursement\n\n \n\n\nCOMPENSATION PHILOSOPHY\n\n - Best offer upfront: Choose from three cash-equity balance options; no negotiation needed\n\n - Top 1% talent: Above-market pay (top 5th percentile) to attract exceptional builders\n\n - High ownership: small teams, \u003e$1M revenue per employee, and significant equity\n\n - Performance-based: Offers tied to interview performance, not tenure or past salary\n\n \n\n\nINTERVIEW PROCESS\n\n - Recruiter screen (15 min)\n\n - SOC 2 audit walkthrough (45 min)\n\n - Hiring Manager interview (45 min)\n\n - Onsite (2 hours)\n   \n   - Security questionnair","salary_min":200000,"salary_max":260000,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["agents","healthcare","speech"],"apply_url":"https://jobs.ashbyhq.com/retell-ai/8a3093dd-35df-435c-bd71-3a0df4246050/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-09-29T23:30:09.439Z","expires_at":"2026-11-13T16:59:08.731347Z","created_at":"2026-10-14T15:22:40.514284Z","updated_at":"2026-10-14T16:59:08.734235Z","company_name":"Retell AI","company_slug":"retell-ai","company_logo_url":"https://www.google.com/s2/favicons?domain=retellai.com\u0026sz=128","quality_score":85,"url":"https://aidevboard.com/job/48455c32-8097-4c20-8ecd-c6e4827ca374"},{"id":"e5cad425-393c-4ed8-ae86-c0f6ff97aeeb","company_id":"95fc9d4d-801c-4800-88aa-1301b340d8f5","title":"Engineering Manager, Trust \u0026 Safety","slug":"engineering-manager-trust-safety-163f2163","description":"Vapi (/ˈVɑːpi/):\n\n - Voice AI that resolves, not transfers\n\n - Powering 1 billion calls for companies like Amazon Ring, Intuit, ServiceTitan, and New York Life\n\n - Trusted by 1 million developers building the future of voice agents\n\n - Backed by Peak XV, Bessemer, Kleiner Perkins, M12, Y Combinator, and more with $72M raised\n\n - Try talking to Vapi now! https://vapi.ai/\n\nWhy We’re Hiring This Role:\n\n - Vapi is scaling fast, and the systems that protect our revenue and customer trust need dedicated engineering leadership. You’ll lead a team of four engineers across billing, fraud, and outbound telephony, with billing, pricing, and packaging making up the largest share of the work.\n\n - Partner closely with our PM for Enterprise \u0026 Governance to set priorities and turn the roadmap into reliable delivery. You’ll strengthen the team’s existing operating rhythm, coach engineers, and own service reliability, on-call, and incident response.\n\n - People leadership is the priority: expect roughly 60–70% people management and 20–30% hands-on building, alongside architecture and code review. The balance can flex with team needs. You’ll shape how the team works and build systems that scale with Vapi.\n\n\n\nWhat You’ll Do:\n\n - 30 Days: Learn our billing, fraud, and outbound telephony systems. Meet each engineer and your product partners, understand current commitments, and assess architecture, service ownership, on-call coverage, and team development needs. Align on the highest-priority gaps.\n\n - 60 Days: Build on existing team routines to strengthen planning and delivery with Product, define service ownership, and strengthen on-call and incident response practices. Guide architecture and code reviews, deliver an initial prioritized improvement, and set clear expectations and growth goals with each engineer.\n\n - 90 Days: Own engineering delivery against a shared roadmap for billing, pricing, packaging, fraud, and outbound telephony. Use delivery and reliability data to prioritize improvements, build actionable development plans for the team, and identify the hiring and system investments needed to scale.\n\n\n\nWho You Are:\n\n - Demonstrated engineering management experience across coaching, performance, leveling, and career development. You can assess promotion readiness, handle difficult people situations, motivate engineers, and hold a team accountable for results.\n\n - Experience designing scalable, reliable enterprise systems and leading engineers through complex technical problems. Billing systems experience is a strong plus; AI expertise is not required.\n\n - Strong hands-on coding, architecture, and system design skills. You bring informed opinions to code review, evaluate tradeoffs, and earn the team’s trust through technical depth.\n\n - Experience owning reliable services and improving on-call and incident response practices. Experience hiring and building a small engineering team is a plus.\n\n - Experience partnering with a PM, with clear judgment about Product and Engineering responsibilities. You can translate product requirements into technical plans and work through disagreements constructively.\n\n - Experience in trust and safety, fraud/risk, voice/telephony, or outbound-call compliance is a plus, as is experience scaling a newly formed team.\n\n\n\nHow We Work:\n\n - Build something worthy of love\n   \n   - Craft matters. We aim to build products and experiences customers genuinely love, not just tolerate.\n\n - Commit and follow through\n   \n   - We finish what we start and build trust by being people others can count on.\n\n - Why not today?\n   \n   - We value urgency and momentum. The fastest path to customer value usually wins.\n\n - Seek raw input\n   \n   - We go directly to customers, data, and teammates instead of relying on summaries or assumptions.\n\n - It’s our problem\n   \n   - We operate as one team. We share credit, own mistakes together, and support each other when things get hard.\n\n - Be direct and kind\n   \n   - We give feedback clearly, respectfully, and without delay.\n\n\n\nWhy Vapi:\n\n - Generational impact: Build the human interface for every business\n\n - Ownership culture: Many of us are previous founders\n\n - Kind team: The founders, Jordan and Nikhil, are Canadians\n\n - Tier-1 Investors: YC, KP seed, Bessemer\n\n\n\nWhat We Offer:\n\n - Real stake: Annual base salary of $264,000–$297,000, plus equity\n\n - Comprehensive health coverage: medical, dental, and vision plans\n\n - Team love: We love hanging out, and we do quarterly off-sites\n\n - Flexible time off: take what you need\n\n - More: catered meals, transportation, equipment, and a $10k annual L\u0026D budget","salary_min":264000,"salary_max":297000,"location":"San Francisco, CA","workplace":"remote","remote_scope":"unknown","job_type":"full-time","experience_level":"lead","tags":["payments","speech","rust"],"apply_url":"https://jobs.ashbyhq.com/vapi/c0431a81-0640-483a-8605-f5cbf1fc45e7/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-09-23T17:12:32.534Z","expires_at":"2026-11-13T16:59:09.348705Z","created_at":"2026-10-14T15:22:41.109259Z","updated_at":"2026-10-14T16:59:09.351455Z","company_name":"Vapi","company_slug":"vapi","company_logo_url":"https://www.google.com/s2/favicons?domain=vapi.ai\u0026sz=128","quality_score":85,"url":"https://aidevboard.com/job/e5cad425-393c-4ed8-ae86-c0f6ff97aeeb"},{"id":"14d08aa6-ef06-41aa-92a3-1389d23f4e8d","company_id":"95fc9d4d-801c-4800-88aa-1301b340d8f5","title":"Member of Technical Staff, Agentic Release Engineer","slug":"member-of-technical-staff-release-engineer-d0336c79","description":"Vapi (/ˈVɑːpi/):\n\n - Voice AI that resolves, not transfers\n\n - Powering 1 billion calls for companies like Amazon Ring, Intuit, ServiceTitan, and New York Life\n\n - Trusted by 1 million developers building the future of voice agents\n\n - Backed by Peak XV, Bessemer, Kleiner Perkins, M12, Y Combinator, and more with $72M raised\n\n - Try talking to Vapi now! https://vapi.ai/\n\nWhy We’re Hiring This Role:\n\n - Vapi ships hundreds of pull requests a day while serving some of the world’s largest enterprises. Every release must stay fast, safe, observable, and predictable at scale.\n\n - Our CI and deployment systems are critical product infrastructure. We need a senior/staff engineer to remove bottlenecks, repair fragile deploy paths, and increase confidence without slowing product teams.\n\n - You’ll own the systems behind safe releases, including Argo CD, Terraform, and Atlantis—and automate the reliable path. This role focuses on CI/CD, testing, and deployment safety, not primary incident response.\n\n\n\nWhat You’ll Do:\n\n - 30 Days: Map Vapi’s release architecture end to end. Partner with product and infrastructure engineers, baseline CI/test/deploy performance, identify the biggest failure modes, and ship an initial improvement.\n\n - 60 Days: Own the release-tooling roadmap and operating health. Remove the costliest CI/deploy bottlenecks, improve observability and diagnosis, and automate slow or failure-prone workflows.\n\n - 90 Days: Establish a repeatable model for safe, fast releases with measurable gains in validation time, deploy speed, and reliability. Deliver self-service workflows and guardrails, and set the longer-term release-infrastructure roadmap.\n\n\n\nWho You Are:\n\n - Evidence of owning critical CI/CD or release infrastructure at meaningful scale and driving measurable cross-team improvements. We care about impact, not a specific number of years.\n\n - Strong distributed-systems fundamentals and the ability to diagnose failures across build, test, deployment, and infrastructure layers.\n\n - Hands-on experience operating Kubernetes-based delivery systems and infrastructure-as-code tooling such as Argo CD, Terraform, and Atlantis or comparable systems.\n\n - A habit of automating repetitive work, investing in testing and passive defenses, and using data to prove that a system became faster or more reliable.\n\n - Deep curiosity and the ability to gather context quickly, form a clear point of view, and keep pace as the architecture and product evolve.\n\n - A low-ego teammate who communicates clearly and owns outcomes. Familiarity with AI coding tools is expected; experience as an SRE, with development frameworks like multi-agent workflows, and programming languages like TypeScript and Go are a plus.\n\n - This is a full-time, hybrid role in San Francisco.\n\n\n\nHow We Work:\n\n - Build something worthy of love\n   \n   - Craft matters. We aim to build products and experiences customers genuinely love, not just tolerate.\n\n - Commit and follow through\n   \n   - We finish what we start and build trust by being people others can count on.\n\n - Why not today?\n   \n   - We value urgency and momentum. The fastest path to customer value usually wins.\n\n - Seek raw input\n   \n   - We go directly to customers, data, and teammates instead of relying on summaries or assumptions.\n\n - It’s our problem\n   \n   - We operate as one team. We share credit, own mistakes together, and support each other when things get hard.\n\n - Be direct and kind\n   \n   - We give feedback clearly, respectfully, and without delay.\n\n\n\nWhy Vapi:\n\n - Generational impact: Build the human interface for every business\n\n - Ownership culture: Many of us are previous founders\n\n - Kind team: The founders, Jordan and Nikhil, are Canadians\n\n - Tier-1 Investors: YC, KP seed, Bessemer Series A\n\n\n\nWhat We Offer:\n\n - Real stake: $235,000–$280,000 base salary, plus meaningful equity ownership\n\n - Comprehensive health coverage: medical, dental, and vision plans\n\n - Team love: We love hanging out, and we do quarterly off-sites\n\n - Flexible time off: take what you need\n\n - More: catered meals, transportation, equipment, and a $10k annual L\u0026D budget","salary_min":235000,"salary_max":280000,"location":"San Francisco, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["speech","agents"],"apply_url":"https://jobs.ashbyhq.com/vapi/250ac759-97a6-46b8-ad7c-9bb4f223dd26/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-09-22T02:01:39.047Z","expires_at":"2026-11-13T16:59:09.339269Z","created_at":"2026-08-29T13:43:07.958916Z","updated_at":"2026-10-14T16:59:09.342045Z","company_name":"Vapi","company_slug":"vapi","company_logo_url":"https://www.google.com/s2/favicons?domain=vapi.ai\u0026sz=128","quality_score":85,"url":"https://aidevboard.com/job/14d08aa6-ef06-41aa-92a3-1389d23f4e8d"}],"page":1,"per_page":20,"total":190,"total_is_exact":true,"total_pages":10}