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Posted 2 days agoApplied AI Engineer, GTM Growth Engineering
at openai
San Francisco, United StatesOn-site
Requirements
- About the Team GTM 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.
- We 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.
- Our work brings together software engineering, applied AI, product, data, and GTM operations.
- About the Role We're looking for an Applied AI Engineer to build production systems that help AI-powered go-to-market workflows improve over time.
- Experience building AI agents, LLM-powered applications, or other model-driven workflows that operated on real production traffic. -
- experience with evaluation design, regression testing, human or model grading, online quality signals, or controlled experiments.
- - Strong backend engineering skills across Python, APIs, data pipelines, stateful workflows, and production services.
- - The ability to work closely with technical and non-technical partners across Engineering, Product, Data Science, Sales, and B2B Marketing.
- You Might Thrive If - You want to build AI systems that improve from real usage instead of stopping at a successful prototype.
- - You are comfortable moving between applied AI, backend engineering, experimentation, and product judgment.
- Experience building agent evaluation, observability, experimentation, or AI infrastructure products. -
- Experience with production replay, LLM grading, human-labeled datasets, shadow evaluation, or staged rollout. -
- Experience with sales, B2B marketing, revenue, CRM, campaign, or other GTM-facing systems. -
- About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence
Additional details
- We measure success through the quality of customer engagement, pipeline, conversion, and the effectiveness of our sales and marketing teams.
- 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.
- This 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.
- You 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. In this role,
- experience building reliable production systems. -
- Experience diagnosing and improving agent behavior using production traces, user feedback, evaluation, experimentation, or careful systems design. - Practical
- - Strong product judgment and the ability to connect technical changes to customer experience, conversion, qualified pipeline, or operational efficiency.
- - Comfort working across model behavior, context, knowledge, tools, workflow state, and human-in-the-loop decisions.
- - A pragmatic mindset: you can scope ambiguous problems, ship useful improvements, and build toward a durable system.
- - You enjoy tracing messy production failures back to the decision, context, tool interaction, or workflow issue that caused them.