Lead AI Native Engineer

RoboForce; Milpitas (CA); On-site; USD 180,000 - 260,000; Full time

Benefits offered by this job

Stock options

Health insurance

Visa sponsorship

Team events

401(k)

Job summary

RoboForce in Milpitas, CA is seeking a Lead AI Native Engineer to turn frontier models into production-ready systems. You will build vertical agents and a shared agent foundation, write code, set architecture, and enable agent development for practical, scalable uses.

This is a hands-on technical leadership role reporting to the co-founder, focusing on evaluation, reliability, and collaboration with research, software, hardware, and data teams to push automations at scale.

Qualifications

• 5+ years in software engineering, applied AI, ML systems or related field.
• Experience shipping production agentic systems relied on by real users.
• Deep experience with frontier model APIs, tools, orchestration, retrieval, memory, and multi-step workflows.
• Strong product judgment and ability to turn ambiguous workflows into secure, measurable systems.

Responsibilities

• Own end-to-end development of vertical agents for high-value workflows across research, software, hardware, data, and operations.
• Build reusable primitives for models, tools, orchestration, context, memory, retrieval, permissions, and long-running execution.
• Create the context layer by connecting agents to trusted data via APIs, pipelines, and integrations with clear provenance and access control.
• Lead evaluation, benchmarks, tracing, monitoring, and failure-analysis loops across quality, latency, cost, security, and resilience.
• Advance frontier agent usage by evaluating new models, coding agents, SDKs, and patterns, turning capabilities into maintainable systems.

Job description

RoboForce is an AI robotics company developing Physical AI-powered Robo-Labor for dull, dirty, and dangerous work. We are not just building AI robots. We are building an AI-native company.

We are hiring a Lead AI Native Engineer 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.

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 through 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 rather than demos.
• Support strategic initiatives. Help company leadership apply agents and analytical systems to market and 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 technical team.

Requirements

• 5+ years in software engineering, applied AI, ML systems, or a related field, with 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.
• A track record shipping production agentic systems that real users depend on—not only prompts, prototypes, or demos.
• Deep experience with frontier model APIs, 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.
• 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.
• Strong product judgment: able to turn an ambiguous decision or workflow into a useful, secure, measurable system.
• 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.
• Competitive stock options/equity programs.
• Health, dental, and vision insurance, 401(k) plan.
• Visa sponsorship and green card support for qualified candidates.
• Lunches and dinners, a fully stocked kitchen, and regular team-building events.