Lead AI Native Engineer

Embedding VC; Milpitas (CA); On-site; USD 180,000 - 280,000; Full time

Benefits offered by this job

Stock options/equity

Health, dental, and vision insurance

Visa sponsorship and green card

Meals and team events

Job summary

RoboForce, an AI robotics company, is hiring a Lead AI Native Engineer in Milpitas, CA to build vertical agents and a 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. Join a team delivering real-world industrial AI deployments.

Qualifications

• 5+ years in software engineering, applied AI, ML systems, or a related field.
• Experience at a frontier AI lab or AI company is a plus.
• Track record shipping production agentic systems with real users.

Responsibilities

• Build vertical agents and end-to-end workflows across domains.
• Establish the agent foundation with reusable primitives and tooling.
• Create the context layer connecting agents to trusted data with provenance.
• Own evaluation, observability, and failure-analysis loops for AI systems.
• Advance frontier agent usage and turn capabilities into maintainable systems.
• Support strategic initiatives for market intelligence and partnerships.
• Provide technical leadership, set architecture, and maintain coding standards.

Skills

Software engineering

Applied AI/ML systems

Frontier AI

Production agentic systems

In-office collaboration

Tools

Claude Code

Codex

Cursor

agent SDKs

MCP infrastructure

Job 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.