Fresh has partnered with an AI Manufacturing software company, we're seeking an experienced senior development operations (DevOps) engineer to own the build, test, and deployment pipeline for our distributed computer vision platform running at edge sites across customer manufacturing floors. This is a full-time position working directly with our engineering team to harden our release process, drive deployment automation, and pioneer LLM-driven test generation and validation.
What You'll Do
- Own and evolve the end-to-end release pipeline - branching strategy, build orchestration, artifact promotion, and rollback - across our Bazel monorepo and Python deployable units
- Design and maintain Ansible-driven fleet automation for heterogeneous Linux edge nodes (Ubuntu LTS, NVIDIA driver stacks, Docker with NVIDIA runtime)
- Manage all update tooling, currently written in Golang
- Build LLM-powered automated testing systems: test generation from specs, flake triage, log/failure analysis, regression diffing, and release-note synthesis from commit and ticket history
- Harden CI/CD for offline and bandwidth-constrained deployment targets (airgap wheel distribution, signed artifacts, deterministic builds)
- Drive observability for releases - deployment telemetry, version drift detection, and post-deploy health validation across the fleet
- Mentor engineers on release hygiene, reproducible builds, and infrastructure-as-code practices
What We're Looking For
- 10+ years of professional experience in release engineering, DevOps, or SRE roles shipping production Linux systems
- Deep curiosity for software, infrastructure, and applied AI - particularly using LLMs as production engineering tools, not just chat assistants
- Expert-level Python (3.8+) with a strong grasp of packaging, dependency resolution, and PEP 440 versioning discipline
- Demonstrated ownership of Linux fleets at scale - kernel, systemd, networking, package management
- Excellence in technical communication, runbook authorship, and post-incident documentation
- Strong systems thinking - comfortable reasoning about failure modes across hardware, OS, container, and application layers
Required Technical Skills
- Expert proficiency with Ansible (roles, dynamic inventory, idempotent design); working knowledge of Terraform
- Expert proficiency with Docker, including creation and lifecycle management of containers, image hardening, registry management and installing & configuring the NVIDIA container runtime
- Production experience with Linux administration: systemd, networking (VLANs, DHCP, DNS), kernel/driver management (especially NVIDIA/DKMS), package and APT internals
- Strong Python skills focused on tooling, automation, packaging (wheels, pip, private indexes), and subprocess/CI integration
- Proficiency with Git workflows, branching strategies, and modern CI/CD systems (GitHub Actions, GitLab CI, or equivalent)
- Experience designing and operating automated test infrastructure - unit, integration, hardware-in-the-loop, and end-to-end
- Practical experience using LLMs (Anthropic, OpenAI, or local) as part of engineering workflows - test generation, code review augmentation, log analysis, or agentic tooling
Nice to Have
- Bazel or similar monorepo build systems
- Edge or embedded deployment experience
- Tailscale, WireGuard, or zero-trust networking in production
- gRPC/protobuf service ecosystems
- Vault, PKI, or secrets management at fleet scale
- Background in regulated or compliance-driven environments (CMMC, ISO 27001, SOC 2)
Compensation offered will be determined by factors such as location, level, job-related knowledge, skills, and experience. Range $75/hr - $85/hr.
