{"schemaVersion":"jobsearcher.job.v1","id":"ba3429fbb4d334dbb01e3f90","url":"https://jobsearcher.com/jobs/ba3429fbb4d334dbb01e3f90","canonicalUrl":"https://jobsearcher.com/jobs/ba3429fbb4d334dbb01e3f90","title":"Applied AI Software Engineer, GTM Growth Engineering","description":"Applied AI - San Francisco\n\nAbout the Team\n\nGTM Growth Engineering builds AI-native products that help OpenAI's go-to-market and B2B marketing organizations scale with greater speed, intelligence, and operational effectiveness.\n\nWe apply OpenAI models to real business workflows and build the systems that make those applications useful and dependable: customer context, agent behavior, feedback, evaluation, experimentation, and appropriate human oversight.\n\nOur work brings together software engineering, applied AI, product, data, and GTM operations. We measure success through the quality of customer engagement, pipeline, conversion, and the effectiveness of our sales and marketing teams.\n\nAbout the Role\n\nWe're looking for an Applied AI Engineer to build production systems that help AI-powered go-to-market workflows improve over time. You will connect agent behavior, customer and operator feedback, evaluation, experimentation, and business outcomes to make these systems more effective, reliable, and responsive to evolving customer needs.\n\nThis is a deeply technical, cross-functional role with end-to-end ownership of the agent improvement loop: understand production behavior, identify failure modes, improve how the system decides or acts, and validate the resulting impact.\n\nYou will partner with Engineering, Product, Data Science, Sales, and B2B Marketing to turn real-world signals into safer, more effective agent behavior and measurable improvements in customer engagement, conversion, qualified pipeline, and team productivity.\n\nIn this role, you will:\n\nOwn the production improvement loop across agent behavior, customer and operator feedback, evaluation, experimentation, and verified business outcomes.\n\nInstrument agent workflows so model interactions, tool use, decisions, failures, human edits, and downstream outcomes can be understood in context.\n\nDefine meaningful quality standards, representative evaluation datasets, regression coverage, and production monitoring for real GTM workflows.\n\nInvestigate why agents underperform across context, knowledge, instructions, tools, routing, guardrails, or workflow design.\n\nDesign and ship targeted behavior improvements, including changes to prompting, context construction, decision logic, tool use, and human-review paths.\n\nBuild backend services, APIs, data models, and feedback pipelines that make agent behavior observable, steerable, and reproducible.\n\nRun controlled experiments, production replays, or staged rollouts to measure whether changes improve quality and downstream business results.\n\nPartner with Product, Data Science, Sales, and B2B Marketing to prioritize high-value problems and define customer and business success.\n\nShip with appropriate safeguards for privacy, security, reliability, human oversight, and safe operational rollout.\n\nYou might be a great fit if you have:\n\n4+ years of software, backend, applied AI, or product-engineering experience building reliable production systems.\n\nExperience building AI agents, LLM-powered applications, or other model-driven workflows that operated on real production traffic.\n\nExperience diagnosing and improving agent behavior using production traces, user feedback, evaluation, experimentation, or careful systems design.\n\nPractical experience with evaluation design, regression testing, human or model grading, online quality signals, or controlled experiments.\n\nStrong backend engineering skills across Python, APIs, data pipelines, stateful workflows, and production services.\n\nStrong product judgment and the ability to connect technical changes to customer experience, conversion, qualified pipeline, or operational efficiency.\n\nComfort working across model behavior, context, knowledge, tools, workflow state, and human-in-the-loop decisions.\n\nThe ability to work closely with technical and non-technical partners across Engineering, Product, Data Science, Sales, and B2B Marketing.\n\nA pragmatic mindset: you can scope ambiguous problems, ship useful improvements, and build toward a durable system.\n\nYou Might Thrive If\n\nYou want to build AI systems that improve from real usage instead of stopping at a successful prototype.\n\nYou enjoy tracing messy production failures back to the decision, context, tool interaction, or workflow issue that caused them.\n\nYou think evaluation is valuable when it helps teams make better product decisions and improve real outcomes.\n\nYou are comfortable moving between applied AI, backend engineering, experimentation, and product judgment.\n\nYou like partnering with operators, sales teams, and marketers to understand the work your systems need to improve.\n\nYou can move from an ambiguous problem to a focused experiment, measured result, and durable implementation.\n\nYou care about trustworthy deployment, clear human-review paths, and reliable production systems.\n\nNice to Have\n\nExperience building agent evaluation, observability, experimentation, or AI infrastructure products.\n\nExperience with production replay, LLM grading, human-labeled datasets, shadow evaluation, or staged rollout.\n\nExperience improving model or agent behavior through context design, prompting, tools, decision logic, or feedback loops.\n\nExperience with sales, B2B marketing, revenue, CRM, campaign, or other GTM-facing systems.\n\nExperience measuring customer engagement, qualified pipeline, conversion, or operational efficiency.\n\nAbout OpenAI\n\nOpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core the full spectrum of humanity.\n\nWe are an equal opportunity employeration, or other applicable legally protected characteristic.\n\nBackground checks for applicants will be administered in accordance with applicable lawation technology systems and related data security obligations.\n\nTo notify OpenAI that you believe this job posting is non-compliant. No response will be provided to inquiries unrelated to job posting compliance.\n\nWe are committed to providing reasonable accommodations to applicants with disabilities.\n\nAt OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.\n\nCompensation\n\n$266K – $405K + Offers Equity","company":"OpenAI","rawCompany":"openai","city":"Millbrae","state":"CA","isRemote":false,"isActive":true,"createdAt":"2026-08-01T09:02:06.998Z","occupations":[{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"},{"code":"15-1299.00","title":"Computer Occupations, All Other","slug":"computer-occupations-all-other"}],"industries":[{"code":"513210","title":"Software Publishers","slug":"software-publishers"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Applied AI Software Engineer, GTM Growth Engineering","description":"Applied AI - San Francisco\n\nAbout the Team\n\nGTM Growth Engineering builds AI-native products that help OpenAI's go-to-market and B2B marketing organizations scale with greater speed, intelligence, and operational effectiveness.\n\nWe apply OpenAI models to real business workflows and build the systems that make those applications useful and dependable: customer context, agent behavior, feedback, evaluation, experimentation, and appropriate human oversight.\n\nOur work brings together software engineering, applied AI, product, data, and GTM operations. We measure success through the quality of customer engagement, pipeline, conversion, and the effectiveness of our sales and marketing teams.\n\nAbout the Role\n\nWe're looking for an Applied AI Engineer to build production systems that help AI-powered go-to-market workflows improve over time. You will connect agent behavior, customer and operator feedback, evaluation, experimentation, and business outcomes to make these systems more effective, reliable, and responsive to evolving customer needs.\n\nThis is a deeply technical, cross-functional role with end-to-end ownership of the agent improvement loop: understand production behavior, identify failure modes, improve how the system decides or acts, and validate the resulting impact.\n\nYou will partner with Engineering, Product, Data Science, Sales, and B2B Marketing to turn real-world signals into safer, more effective agent behavior and measurable improvements in customer engagement, conversion, qualified pipeline, and team productivity.\n\nIn this role, you will:\n\nOwn the production improvement loop across agent behavior, customer and operator feedback, evaluation, experimentation, and verified business outcomes.\n\nInstrument agent workflows so model interactions, tool use, decisions, failures, human edits, and downstream outcomes can be understood in context.\n\nDefine meaningful quality standards, representative evaluation datasets, regression coverage, and production monitoring for real GTM workflows.\n\nInvestigate why agents underperform across context, knowledge, instructions, tools, routing, guardrails, or workflow design.\n\nDesign and ship targeted behavior improvements, including changes to prompting, context construction, decision logic, tool use, and human-review paths.\n\nBuild backend services, APIs, data models, and feedback pipelines that make agent behavior observable, steerable, and reproducible.\n\nRun controlled experiments, production replays, or staged rollouts to measure whether changes improve quality and downstream business results.\n\nPartner with Product, Data Science, Sales, and B2B Marketing to prioritize high-value problems and define customer and business success.\n\nShip with appropriate safeguards for privacy, security, reliability, human oversight, and safe operational rollout.\n\nYou might be a great fit if you have:\n\n4+ years of software, backend, applied AI, or product-engineering experience building reliable production systems.\n\nExperience building AI agents, LLM-powered applications, or other model-driven workflows that operated on real production traffic.\n\nExperience diagnosing and improving agent behavior using production traces, user feedback, evaluation, experimentation, or careful systems design.\n\nPractical experience with evaluation design, regression testing, human or model grading, online quality signals, or controlled experiments.\n\nStrong backend engineering skills across Python, APIs, data pipelines, stateful workflows, and production services.\n\nStrong product judgment and the ability to connect technical changes to customer experience, conversion, qualified pipeline, or operational efficiency.\n\nComfort working across model behavior, context, knowledge, tools, workflow state, and human-in-the-loop decisions.\n\nThe ability to work closely with technical and non-technical partners across Engineering, Product, Data Science, Sales, and B2B Marketing.\n\nA pragmatic mindset: you can scope ambiguous problems, ship useful improvements, and build toward a durable system.\n\nYou Might Thrive If\n\nYou want to build AI systems that improve from real usage instead of stopping at a successful prototype.\n\nYou enjoy tracing messy production failures back to the decision, context, tool interaction, or workflow issue that caused them.\n\nYou think evaluation is valuable when it helps teams make better product decisions and improve real outcomes.\n\nYou are comfortable moving between applied AI, backend engineering, experimentation, and product judgment.\n\nYou like partnering with operators, sales teams, and marketers to understand the work your systems need to improve.\n\nYou can move from an ambiguous problem to a focused experiment, measured result, and durable implementation.\n\nYou care about trustworthy deployment, clear human-review paths, and reliable production systems.\n\nNice to Have\n\nExperience building agent evaluation, observability, experimentation, or AI infrastructure products.\n\nExperience with production replay, LLM grading, human-labeled datasets, shadow evaluation, or staged rollout.\n\nExperience improving model or agent behavior through context design, prompting, tools, decision logic, or feedback loops.\n\nExperience with sales, B2B marketing, revenue, CRM, campaign, or other GTM-facing systems.\n\nExperience measuring customer engagement, qualified pipeline, conversion, or operational efficiency.\n\nAbout OpenAI\n\nOpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core the full spectrum of humanity.\n\nWe are an equal opportunity employeration, or other applicable legally protected characteristic.\n\nBackground checks for applicants will be administered in accordance with applicable lawation technology systems and related data security obligations.\n\nTo notify OpenAI that you believe this job posting is non-compliant. No response will be provided to inquiries unrelated to job posting compliance.\n\nWe are committed to providing reasonable accommodations to applicants with disabilities.\n\nAt OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.\n\nCompensation\n\n$266K – $405K + Offers Equity","datePosted":"2026-08-01T09:02:06.998Z","dateModified":"2026-08-01T09:02:06.998Z","hiringOrganization":{"@type":"Organization","name":"OpenAI","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Millbrae","addressRegion":"CA","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"ba3429fbb4d334dbb01e3f90"},"url":"https://jobsearcher.com/jobs/ba3429fbb4d334dbb01e3f90"}}