Lead AI-Native Systems Architect

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 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.