AI Software Engineer (Fullstack)
Hybrid · Walnut Creek, California, United States
Job Summary
AI Software Engineer role focused on owning AI agents and workflows end-to-end, from scoping with product and design to prompt/tool design, production deployment, and continuous iteration. Build across the full stack (agent orchestration backends, tool/API integrations, evaluation pipelines, observability, and product surfaces where agents show up). Design and run evals (golden sets, LLM-as-judge, regression evals) to ensure production-quality agents. Integrate with construction-tech ecosystems (accounting systems, project management tools, document repositories) and Clearstory’s BigQuery-backed data platform. Collaborate with product, design, and engineers to convert real-world workflows into reliable agent behaviors. Move fast in a SOC 2–compliant environment using modern AI development workflows. About you: shipped production LLM systems, comfortable in ambiguous environments, genuinely fullstack (Postgres up through React), strong communication, reliability and craft mindset, startup-fast mindset, and alignment with core values Be Curious, Customer Obsession, Keep It Simple. This is a hybrid role with 3 days in the office and 2 days remote per week in Walnut Creek, CA.
Required Qualifications
- 2-3+ years of professional software engineering experience, including production work on AI/LLM systems
- Strong proficiency in Python and TypeScript, including async programming
- Fullstack production experience — React/TypeScript on the frontend, modern backend services, REST APIs, Postgres
- Hands-on experience with modern LLM tooling: prompt engineering, function/tool calling, RAG patterns, vector stores, and at least one major model provider (Anthropic, OpenAI, Google)
- Experience designing and running evaluation frameworks for LLM systems
- Comfort with cloud infrastructure (GCP preferred; AWS or Azure acceptable), Docker, and CI/CD
- Strong written and verbal communication — scope an agent with product, explain tradeoffs to an exec, and write docs your teammates actually want to read
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