Applied AI Software Engineer, GTM Growth Engineering

Job summary

Responsibilities

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…

• 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.

What they're looking for

• 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.

Tech stack

• Python