AI Builder
Build production-grade AI agents, evaluation infrastructure, and developer tooling that make AI-assisted engineering faster, safer, and reusable across teams. The role requires software engineering experience, platform or internal developer-product experience, and hands-on expertise with LLM integration and orchestration.
About the job
Responsibilities
- Design and build production agent systems, including prompts, reasoning chains, tool calls, MCP servers, agent scaffolding, context harnesses, and a skills marketplace.
- Rethink the product development lifecycle by replacing manual friction with governed agentic workflows across scoping, design, review, testing, deployment, and monitoring.
- Build evaluation infrastructure, including pipelines, benchmarks, quality gates, and evaluation harnesses for AI-assisted workflows.
- Establish generation-to-merge and review-latency baselines and make model quality visible and trustworthy across engineering teams.
- Turn successful AI pilots into production-ready reusable libraries, templates, and reference implementations.
- Partner with architects, domain leads, and product engineers to create tools, patterns, and guardrails for safe AI adoption.
Requirements
- 3+ years of full-time software engineering experience, including at least 2 years building tooling, platforms, or internal developer products.
- Bachelor’s, Master’s, or PhD in Computer Science, Computer Engineering, or a related technical discipline, or equivalent industry experience.
- Hands-on experience with LLM integration patterns, including prompt engineering, RAG pipelines, tool/function calling, and agent architectures.
- Ability to work across the stack when needed.
- Experience with MCP, LangChain, or comparable orchestration frameworks.
- Experience with open-source LLM models.
- Strong developer-experience focus and a record of building tools adopted by other engineers.
Nice to Have
- Reinforcement learning experience, especially RLHF, RLAIF, or reward modeling in applied product contexts.
- Experience in fintech or regulated and security-sensitive environments.
- Hands-on experience with AI governance, including bias evaluation, audit logging, and model cards.
- Exposure to multi-step reasoning pipelines or human-in-the-loop system design.
Compensation
- Mountain View base salary: $189,000–$231,000 per year, plus equity and benefits.
Skills
Prompt Engineering, Retrieval-Augmented Generation, Tool Calling, Agent Architectures, Mcp, LangChain, Open-Source Llms, Reinforcement Learning, RLHF, Rlaif, Reward Modeling, Ai Governance, Audit Logging, Model Cards, Python
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