# Lead AI Native Engineer at RoboForce

Lead AI Native Engineer at RoboForce in Milpitas, CA. On-site. Posted June 11, 2026.

- Company: RoboForce
- Location: Milpitas, CA
- Workplace: On-site
- Experience: 5+ years
- Posted: 2026-06-11
- Apply: https://job-boards.greenhouse.io/roboforce/jobs/5255989008
- Source: https://jobmagic.ai/jobs/lead-ai-native-engineer-roboforce-jc6nw4

## 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.

## Description

**Why RoboForce**

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.

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.

**Benefits**

- 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.