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Applied AI Software Engineer, GTM Growth Engineering

OpenAI

Applied AI Software Engineer, GTM Growth Engineering is a still-open role at OpenAI on Jobrow. Location: On-site · San Francisco · California · United States. Listed pay: $266k–$405k. Sourced from the company's public Ashby board. First seen 2 months ago; last confirmed 9 days ago. Apply on the employer ATS — Jobrow is not the employer.

Pay
$266k–$405k
Workplace
On-site
Location
San Francisco · California · United States
First seen
2 months ago
Last seen
9 days ago
Board
Ashby
Apply

About this role

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.

  • Function: Machine learning
  • Seniority: mid

Location & pay

On-site · San Francisco · California · United States Listed pay on Jobrow: $266k–$405k.

Source

Jobrow reads the public Ashby board for OpenAI. First seen 2 months ago; last seen 9 days ago. We are not the employer — apply only on the company ATS.

Posting

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.   In this role, you will: - 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 rollou

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