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Applied AI Engineer

UMATR
4 hours ago
Full-time
On-site
Sunnyvale, California, United States
About the Role We’re hiring an

Applied AI Engineer

to design and deploy AI-powered automation across the company. This is a highly cross-functional, high-ownership role. You’ll work directly with teams across engineering, research, hardware, and business operations to identify where AI can drive meaningful efficiency gains, and then build the solutions end-to-end.

One week you might design an AI workflow to automate internal research; the next, you’re building tools that give teams instant access to critical data across systems. This role is ideal for someone who thrives in ambiguity, moves quickly, and wants to ship systems people actually rely on.

**We are only able to consider applications from U.S. citizens or Green Card holders due to the nature of the project**

What You’ll Do Design, build, and deploy production-grade AI agents and automation tools Architect reliable, secure, and observable systems Implement human-in-the-loop workflows, feedback loops, and fail-safes Work directly with stakeholders to understand workflows and pain points Conduct interviews and workflow analysis before building Translate insights into scoped, high-impact solutions Own rollout, onboarding, and iteration of tools you build Ensure systems are actually used and deliver value Share best practices for AI adoption across teams Apply strong security practices (access control, data handling, etc.) Write clear documentation (runbooks, APIs, decision logs) Monitor and evaluate system performance

What We’re Looking For Strong CS fundamentals and experience shipping production software Hands-on experience with LLM APIs or AI agent systems Ability to go from problem discovery → solution → deployment Strong product intuition and stakeholder communication skills Security-minded approach to system design

Nice-to-Have Experience building internal tools or operational automation Familiarity with agent patterns (tool use, memory, multi-agent systems) Experience with evaluation/monitoring of AI systems Experience in fast-paced or startup environments

What Success Looks Like You ship AI systems that teams actively depend on Your work measurably improves speed or decision-making Systems you build are maintainable and well-documented You identify and prioritise the next highest-impact opportunities