RoboForce

RoboForce

Lead AI Native Engineer

Milpitas, CA · Senior

Sponsorship not specifiedDetected 7 days ago
Machine LearningRAGAgentic AIRoboticsResearchLeadershipCollaboration

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odds of building a lasting career here

40Risky
Cap-exempt (no lottery)0
Sponsors this role90
Entry-level history0
PERM / green-card track0
Lottery odds40
Fits your clock70

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Employer immigration record

from this employer's Department of Labor filings

Green-card filing pattern in this occupation

Context, not a finding about this posting: of this employer's 3 green-card filings in this occupation, 100% were for a worker who already held the job.

Files H-1B transfers

4 transfer filings in the last year, covering 4 workers. Median labor-condition decision: 7 days. An employer that already files transfers is one that can take over an existing H-1B.

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About the role

  • The company's robots are engineered for demanding industrial environments, with a focus on real-world deployment and scalability.
  • Reporting to the co-founder, you will turn frontier models into systems for strategy and engineering.
  • Help company leadership apply agents and analytical systems to market and customer intelligence, partnerships, fundraising, diligence, scenario analysis, and executive decisions. - Provide technical leadership.

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.
  • 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.
  • 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.
  • RoboForce is an AI robotics company developing Physical AI-powered Robo-Labor for dull, dirty, and dangerous work.
  • Visa sponsorship and green card support for qualified candidates.

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.

Nice to have

  • 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.

Company info

  • We are hiring a Lead AI Native Engineer to build RoboForce's vertical agents and shared agent foundation.

Visa & Work Authorization

  • Visa sponsorship and green card support for qualified candidates.

This listing is sourced directly from RoboForce's careers page and normalized into a canonical job model.