About the Role

Join a team building the AI systems layer for an enterprise process intelligence product. You will turn complex customer data into reliable, useful product capabilities powered by hosted language models.

What You'll Do

Build and own production AI services that transform unstructured enterprise data into structured process intelligence.

Develop retrieval, context construction, structured extraction, and orchestration workflows using hosted AI models.

Create representative evaluation datasets, benchmarks, regression tests, guardrails, and fallback paths to measure and improve AI quality.

Monitor production behavior, investigate incidents, and improve reliability, latency, cost, and recovery.

Use customer feedback to guide product decisions and iterate on features from design through deployment.

Work across the end-to-end system, from raw data and retrieval through generated results and customer-facing behavior.

What We're Looking For

4 to 10 years of applied AI, ML, or production software engineering experience, including sustained ownership of customer-facing systems.

Strong Python service development experience, including asynchronous patterns and integration with AI/ML tools; familiarity with Go or another typed language is useful.

Hands-on experience with hosted LLM APIs, RAG or retrieval, agent orchestration, and production evaluation or benchmark systems.

Experience handling production incidents, debugging failures, and building observable, resilient services and pipelines.

Ability to work directly with customers, incorporate feedback, and communicate clearly in writing and conversation.

Strong systems thinking, pragmatic technical judgment, and experience delivering external products, including early-stage or 0-to-1 work.

A bachelor's degree or higher in computer science, engineering, or a related technical field; experience with multimodal or enterprise document data is a plus.

Compensation & Benefits

Base salary: $180,000 to $275,000 annually. Visa sponsorship is available.

Location

On-site in San Francisco, California.