Infrastructure Engineer

AI Infrastructure Engineer — Hardware Systems

We’re working with an early-stage AI company applying advanced AI agents to semiconductor engineering.

They’re hiring an infrastructure engineer who combines strong software and platform fundamentals with enough hardware knowledge to understand chip-design workloads. You’ll build the environments, tooling and data infrastructure that allow AI agents to interact reliably with complex engineering tools.

What you’ll work on

• Build containerized and virtualized environments for hardware workflows
• Create infrastructure for running and evaluating AI agents at scale
• Integrate engineering tools into reliable, reproducible execution environments
• Develop internal tooling that improves researcher and engineer productivity
• Support data generation, filtering and evaluation workflows
• Build observability, testing and failure-recovery into agent infrastructure
• Work across AI research, software infrastructure and semiconductor engineering

What we’re looking for

• 2–8 years of software or infrastructure engineering experience
• Strong Python and practical experience with Docker, containers and VMs
• Regular use of AI coding agents such as Claude Code or Cursor
• Exposure to digital design, VLSI, FPGA, verification, EDA or semiconductor tooling
• Working knowledge of machine-learning concepts
• Adaptability and comfort building without mature internal platforms

Experience with reinforcement learning, synthetic task generation, agent evaluation, developer productivity or post-training data would be particularly useful.

This role suits someone who wants infrastructure ownership but also wants to work much closer to AI research and hardware engineering than a conventional platform position allows.