Lead AI Native Engineer
Embedding Vc · Milpitas, CA
About this role
## Lead AI Native Engineer ### About RoboForce RoboForce is an AI robotics company building **Physical AI-powered Robo-Labor** for dull, dirty, and dangerous work. Our robots are engineered for demanding industrial environments, with a focus on **real-world deployment and scalability**. You’ll join as a **hands-on technical leader** to build RoboForce’s **vertical agents** and a **shared agent foundation**—turning frontier models into production systems for strategy and engineering. --- ### Responsibilities - **Build vertical agents**: Own end-to-end agents for high-value workflows across research, software, hardware, data, and operations—from problem definition through production use. - **Establish the agent foundation**: Build reusable primitives for models, tools, orchestration, context, memory, retrieval, permissions, human approval, and long-running execution. - **Create the context layer**: Connect agents to trusted data via APIs, pipelines, MCP servers, and integrations with clear provenance and access control. - **Own evaluation and reliability**: Build benchmarks, regression tests, tracing, monitoring, and failure-analysis loops across quality, latency, cost, security, and resilience. - **Advance frontier agent usage**: Evaluate new models, coding agents, SDKs, and patterns—then turn useful capabilities into maintainable systems (not demos). - **Support strategic initiatives**: Help leadership apply agents and analytical systems to market/customer intelligence, partnerships, fundraising, diligence, scenario analysis, and executive decisions. - **Provide technical leadership**: Set architecture and engineering standards, review designs and code, and create reusable patterns for the team. --- ### Requirements - **5+ years** in software engineering, applied AI, ML systems, or related field; strong **zero-to-one** technical judgment. - Experience at a **frontier AI lab**, leading AI company, or comparable team working at the edge of current model capabilities. - Track record shipping **production agentic systems** used by real users—not just prompts/prototypes/demos. - Deep experience with frontier model APIs and **tool use, orchestration, context engineering, retrieval, memory, and multi-step workflows**. - Experience building **evaluations, regression tests, observability, and production failure-analysis loops** for AI systems. - Strong fluency with **AI-native development workflows** (e.g., Claude Code, Codex, Cursor, agent SDKs or equivalents) and a rigorous understanding of where agents work and fail. - Strong product judgment: turn ambiguous workflows into **useful, secure, measurable** systems. - **Requires 5 days/week in-office** collaboration with the team. --- ### Bonus Qualifications - Experience with **post-training, model evaluation, inference, or research infrastructure** at a frontier lab or model company. - Experience with **MCP infrastructure**, developer platforms, knowledge graphs, RAG, or secure enterprise integrations. - Background in **robotics, autonomous systems, industrial automation**, or another technically complex physical-world domain. --- ### Benefits - Competitive **stock options/equity** - Health, dental, and vision insurance; **401(k)** plan - **Visa sponsorship** and green card support for qualified candidates - Lunches/dinners, fully stocked kitchen, and regular team-building events
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