Systems Engineer

Atomic Industries is reinventing how the world makes things. From cars and aerospace systems to medical devices and packaging, most physical goods begin life in a mold or are shaped by a manufacturing tool. Producing these tools has always been slow, manual, and dependent on scarce expertise, taking weeks or months. We’re changing that.

At our Detroit headquarters, we combine the industrial DNA of America’s manufacturing heartland with the speed, intelligence, and precision of Silicon Valley. Our AI-driven platform tackles the hardest problems in geometry, process planning, and fabrication, collapsing production timelines from months to days and soon, minutes. We don’t just build software; we run a fully operational factory where our technology produces production-grade tooling every week, enabling tight feedback loops and rapid iteration.

Backed by top-tier investors, we’re restoring speed, flexibility, and capability to the American industrial base. Our mission is to make manufacturing as agile and scalable as the digital world, and in doing so, rebuild the infrastructure of the physical economy.

As an Infrastructure Engineer at Atomic, you’ll own the systems that power high-performance simulation, geometry processing, and factory automation. You’ll be responsible for building and maintaining the hybrid infrastructure that spans cloud, on-prem, and GPU compute environments.

This role is ideal for engineers who thrive at the intersection of reliability, performance, and engineering velocity.

Manage and improve CI/CD pipelines (GitHub Actions, Terraform, HashiCorp stack)

Orchestrate compute workloads across cloud and bare-metal GPU clusters

Design systems for secure, fault-tolerant deployment and observability

Build internal tooling to accelerate developer workflows and operations

Partner with engineers on simulation, ML, and backend teams to scale infrastructure

Monitor and tune system performance under high computational loads

5+ years in DevOps, infrastructure, or site reliability engineering

Proficiency with container orchestration (Nomad, Kubernetes), IaaC, and Linux

Strong scripting and programming skills (Python, Bash, Go)

Experience with hybrid (cloud + on-prem) infrastructure

Familiarity with distributed systems, caching layers, and observability tools

Background supporting ML, simulation, or HPC workloads

Experience managing large GPU fleets or multi-node compute tasks

Security or compliance experience (ITAR, SOC2, CMMC)

Track record of building tooling for high-autonomy engineering teams

Fast iteration: We deploy code daily and validate it in the factory every week

Factory-first mindset: Engineers spend time on the shop floor to understand the real-world impact of their work

Low ceremony, high ownership: We value well-written design docs, tested code, and real results — not meetings

Collaborative culture: Geometry, AI, and robotics teams are tightly integrated and co-develop the product together