Quick overview
Job description
About the Role
Join an applied AI team building the systems layer for an enterprise process intelligence platform. You will make AI behavior reliable, measurable, and useful in production, using hosted frontier models and real customer data.
What You'll Do
Build and operate Python services and AI pipelines, including retrieval, context construction, structured extraction, orchestration, and model or provider selection.
Develop evaluation datasets, benchmarks, regression tests, guardrails, and fallback paths to measure and improve AI quality.
Monitor production systems and address latency, cost, reliability, and failure handling.
Trace end-to-end data flows from raw enterprise sources to generated outputs and user-facing product behavior.
Use customer feedback and observed product performance to iterate on features and ship improvements.
Make pragmatic decisions about architecture, technical debt, and when to build or adopt existing tools.
What We're Looking For
4 to 10 years of applied AI or ML engineering experience, including shipping and maintaining production systems for external customers.
Strong Python skills, experience with Go, asynchronous services, and AI/ML tooling.
Hands-on experience with hosted LLM APIs, RAG or retrieval, structured outputs, tool use, or multi-step agent workflows.
Experience building AI evaluations or benchmarks and improving system quality through testing, monitoring, and customer feedback.
Production software engineering experience across the AI lifecycle, from data and context preparation to user-facing product behavior.
Strong systems thinking, ownership, and communication skills, with experience building products in a startup or similarly fast-moving environment.
A bachelor's degree or higher in computer science, engineering, or a related technical field.
Experience with document understanding, multimodal data, enterprise workflows, or typed languages is helpful.
Compensation & Benefits
Base salary: $180,000 to $275,000 USD annually. Visa sponsorship is available.
Location
On-site in San Francisco, California, United States.
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