Senior Open Source Infrastructure Engineer

Role Description

Quansight is looking for a full-time remote Senior Infrastructure Engineer to join our team of open-source experts and software engineering professionals. This is a high-ownership, high-autonomy role where you will apply core infrastructure engineering principles such as scalability, observability, reliability, and automation across both internal systems and client engagements.

• Own Quansight's internal cloud infrastructure while serving as the technical lead on client-facing infrastructure engagements.
• Help clients design, implement, and maintain reliable, scalable solutions.
• Transfer knowledge to client teams so they can own what you build.
• Participate actively in open-source communities as a maintainer or contributor.
• Allocate between 40 and 50 percent of structural time to continue contributing to and maintaining existing open-source infrastructure projects.

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.

Requirements

• 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.

Benefits

• Flexibility in work times and locations.
• Vacation time is encouraged, celebrated, and enforced.
• Competitive compensation.
• Comprehensive sick policy and parental leave.
• A generous amount of flexible paid time off.
• Comprehensive benefits package for applicants located in the United States, Canada, Germany, or the UK.