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OpenAI's GTM Growth Engineering team is building AI-native products that help the company's go-to-market and B2B marketing organizations scale with greater speed, intelligence, and operational effectiveness. This Applied AI Engineer role focuses on building production systems that improve AI-powered go-to-market workflows over time.
You will own the end-to-end agent improvement loop: understanding production behavior, identifying failure modes, improving system decisions and actions, and validating impact. This deeply technical, cross-functional role requires connecting agent behavior, customer and operator feedback, evaluation, experimentation, and business outcomes to make systems more effective, reliable, and responsive to evolving customer needs.
Key responsibilities include:
- Owning the production improvement loop across agent behavior, feedback, evaluation, experimentation, and verified business outcomes
- Instrumenting agent workflows to understand model interactions, tool use, decisions, failures, and downstream outcomes
- Defining quality standards, evaluation datasets, regression coverage, and production monitoring for GTM workflows
- Investigating agent underperformance across context, knowledge, instructions, tools, routing, and workflow design
- Designing and shipping targeted behavior improvements through prompting, context construction, decision logic, and tool use changes
- Building backend services, APIs, data models, and feedback pipelines for observable and steerable agent behavior
- Running controlled experiments and staged rollouts to measure quality and business impact
- Partnering with Product, Data Science, Sales, and B2B Marketing to prioritize high-value problems
- Shipping with appropriate safeguards for privacy, security, reliability, and human oversight
Ideal candidates have 4+ years of software, backend, applied AI, or product-engineering experience building reliable production systems. You should have experience building AI agents or LLM-powered applications on real production traffic, diagnosing and improving agent behavior using production traces and evaluation, and strong backend engineering skills in Python, APIs, and data pipelines. Product judgment connecting technical changes to customer experience and conversion is essential. Experience with agent evaluation, observability, production replay, LLM grading, or sales/B2B marketing systems is a plus.
