Product Engineer, GTM Growth Engineering

About the Team GTM Growth Engineering builds autonomous and semi-autonomous AI systems that help OpenAI's go-to-market organization operate at massive scale. We design agents and product systems that reason over messy GTM context, identify high-value opportunities, prioritize accounts and leads, route judgment-heavy work, take routine actions, and learn from every outcome. Our mandate is revenue leverage: systems directly tied to pipeline quality, revenue execution, sales productivity, and the speed at which OpenAI can bring its products to the world. The work sits at the intersection of product engineering, applied AI, data, and GTM operations. The team builds the infrastructure and user experiences for agentic revenue workflows: signal quality, prioritization, routing, attribution, review queues, feedback loops, evals, and measurement. We focus on problems that need native product craft, deep system integration, and high standards for autonomy, reliability, safety, privacy, and operational simplicity. About the Role We're looking for a product engineer to help build highly autonomous agentic systems for GTM Growth Engineering. You will own meaningful product slices end to end: agent workflows, user experience, frontend implementation, backend APIs and services, data and state models, model and tool integrations, telemetry, evals, and launch readiness. This is a role for engineers who want to build AI systems that do real work in production. You will partner with product, design, data, research, operations, and customer-facing teams to understand high-value workflows, define success metrics, and ship systems that improve pipeline quality, revenue execution, sales productivity, operational throughput, customer experience, and learning velocity. The role is ideal for a strong product engineer who can move between product craft, agent behavior, systems engineering, and measurable business outcomes. You should be excited to build from ambiguous problem statements, ship quickly, and harden systems that operate with increasing autonomy at scale. What You'll Do - Build autonomous and semi-autonomous GTM systems that identify opportunities, recommend or take next actions, route work, and learn from outcomes at scale. - Own full-stack product slices from prototype through launch, hardening, instrumentation, evals, and iteration. - Design agent workflows that combine LLM reasoning, tools, structured data, human oversight, and feedback loops. - Create intuitive surfaces for humans to supervise, review, correct, and improve AI-driven workflows. - Build reliable backend services, APIs, data flows, and stateful product surfaces that integrate with internal tools and customer-facing systems. - Design feedback loops, evals, quality metrics, and launch-readiness criteria for AI systems that affect revenue and pipeline outcomes. - Partner with product, design, data, research, sales, marketing, operations, support, and other GTM stakeholders to ship trustworthy products. - Instrument the experience so we can understand usage, friction, quality, adoption, business impact, and operational health. - Make pragmatic tradeoffs across autonomy, speed, quality, scalability, privacy, safety, and supportability in 0-to-1 product areas. What We're Looking For - Have 4+ years of experience as a software, product, or full-stack engineer building high-quality user-facing products. - Strong frontend or full-stack engineering skills, with comfort across modern web apps, APIs, data models, stateful user flows, and instrumentation. - Strong product judgment and a track record of turning ambiguous ideas into shipped product. - Experience building in 0-to-1 or fast-moving product environments where user needs, product shape, and success metrics are still being discovered. - Excitement about building AI systems that take action, use tools, make recommendations, coordinate with humans, and improve from feedback. - A high bar for UX quality, interaction details, accessibility, reliability, and user empathy. - Ability to use qualitative feedback, evals, and product data to identify friction, prioritize work, and improve outcomes. - Clear written and verbal communication, especially when simplifying complex technical concepts for different audiences. - Careful judgment when building AI-powered products that sit close to users, business processes, and operational decisions. You Might Thrive If - You want to build agentic systems that own real business outcomes from prototype through scaled operation. - You are excited by products where agents, humans, and data work together in live operational workflows. - You like product work where the right answer is discovered through shipping, measurement, and iteration. - You can move between prototype speed and production-quality engineering without losing sight of the user or the business metric. - You enjoy working with non-engineering partners and turning domain expertise into clear