Senior Open Source Infrastructure Engineer
RemoteUnited States
Job Summary
Own and evolve Quansight's cloud infrastructure across AWS, Azure, and GCP, ensuring reliable day-to-day operation. Build, deploy, and maintain internal dashboards and reporting for operations, including system architecture documentation. Lead infrastructure engagements for clients from scoping through delivery, upskilling client teams to maintain the solutions you build. Contribute to open-source projects and participate in upstream communities, with 40 to 50 percent of your structural time allocated to this work. Mentor teammates on infrastructure practices and contribute to Quansight's technical presence through talks and RFCs. This high-ownership role requires 5+ years of infrastructure experience and production familiarity with at least two of AWS, Azure, and GCP.
Required Qualifications
- 5+ years of experience in infrastructure, DevOps, or platform engineering
- Open-source experience as a maintainer or sustained contributor
- Ability to independently scope, architect, and execute infrastructure projects end-to-end
- Production experience across at least two of AWS, Azure, and GCP
- Strong proficiency with infrastructure-as-code tools such as Terraform, Pulumi, or CloudFormation
- Experience managing containerized workloads on Kubernetes, including Helm chart development
- Experience building and maintaining CI/CD pipelines (GitHub Actions, GitLab CI/CD, CircleCI, or equivalent)
- Hands-on experience with observability tooling such as Prometheus, Grafana, and/or the ELK/OpenSearch stack
- Familiarity with cloud security best practices, including secrets management, IAM/RBAC, and pipeline security scanning
- Proficiency in Python or another general-purpose language for scripting and automation
- Client-facing experience: translating requirements into infrastructure designs, communicating technical decisions to non-technical stakeholders, and managing expectations
- Fluency with Git and GitHub for version control, code review, and asynchronous collaboration across a distributed remote team
- Ability to constructively receive and act on feedback
- Time overlap with U.S. and European time zones
Desired Qualifications
- Experience with GitOps workflows and tools such as ArgoCD or Flux
- Experience with data science workflows, platforms, data management practices and MLOps
- Experience with configuration management tools such as Ansible
- Experience with SQL and database management
- Familiarity with the PyData ecosystem
- Experience deploying AI/ML workloads in production - GPU orchestration on Kubernetes, model-serving frameworks (KServe, Ray Serve, vLLM, Triton), or LLM inference infrastructure
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