Lead AI Native Engineer at RoboForce

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