Applied AI Software Engineer, GTM Growth Engineering
Primary stack
Nice to have's
Job description
About the Position
Applied AI Software Engineer, GTM Growth Engineering
San Francisco
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. We measure success through the quality of customer engagement, pipeline, conversion, and the effectiveness of our sales and marketing teams.
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. 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.
Responsibilities
- Own the production improvement loop across agent behavior, customer and operator feedback, evaluation, experimentation, and verified business outcomes.
- Instrument agent workflows so model interactions, tool use, decisions, failures, human edits, and downstream outcomes can be understood in context.
- Define meaningful quality standards, representative evaluation datasets, regression coverage, and production monitoring for real GTM workflows.
- Investigate why agents underperform across context, knowledge, instructions, tools, routing, guardrails, or workflow design.
- Design and ship targeted behavior improvements, including changes to prompting, context construction, decision logic, tool use, and human-review paths.
- Build backend services, APIs, data models, and feedback pipelines that make agent behavior observable, steerable, and reproducible.
- Run controlled experiments, production replays, or staged rollouts to measure whether changes improve quality and downstream business results.
- Partner with Product, Data Science, Sales, and B2B Marketing to prioritize high-value problems and define customer and business success.
- Ship with appropriate safeguards for privacy, security, reliability, human oversight, and safe operational rollout.
Requirements
- 4+ years of software, backend, applied AI, or product-engineering experience building reliable production systems.
- Experience building AI agents, LLM-powered applications, or other model-driven workflows that operated on real production traffic.
- Experience diagnosing and improving agent behavior using production traces, user feedback, evaluation, experimentation, or careful systems design.
- Practical 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.
- 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.
- The ability to work closely with technical and non-technical partners across Engineering, Product, Data Science, Sales, and B2B Marketing.
- A pragmatic mindset: you can scope ambiguous problems, ship useful improvements, and build toward a durable system.
Nice to Have
- 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 improving model or agent behavior through context design, prompting, tools, decision logic, or feedback loops.
- Experience with sales, B2B marketing, revenue, CRM, campaign, or other GTM-facing systems.
- Experience measuring customer engagement, qualified pipeline, conversion, or operational efficiency.
We Offer
- Competitive salary
- Opportunity to work in a cutting-edge AI research and deployment company
- Collaborative and inclusive work environment
- Professional growth and development opportunities
About the Company
OpenAI 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, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.
We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.
For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.
Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates.
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