Scientific Platform Engineer

Company Description

By working at Harvard University, you join a vibrant community that advances Harvard's world‑changing mission in meaningful ways, inspires innovation and collaboration, and builds skills and expertise. We are dedicated to creating a diverse and welcoming environment where everyone can thrive.

Harvard Medical School's mission is to nurture a diverse, inclusive community dedicated to alleviating suffering and improving health and well‑being for all through excellence in teaching and learning, discovery and scholarship, and service and leadership.

You’ll be at the heart of biomedical discovery, education, and innovation, working alongside world‑renowned faculty and a community dedicated to improving human health. This is more than a job – it’s an opportunity to shape the future of medicine.

The SBGrid Consortium at Harvard Medical School supports a large international research community by curating and distributing a scientific software platform used across structural biology, cryo‑EM, and related fields. The platform includes approximately 650 software titles and 6,000 versions across macOS and Linux and is deployed across laptops, workstations, HPC clusters, and cloud environments. We are hiring a Scientific Platform Engineer to help lead the modernization, security, reliability, and engineering evolution of this platform.

This is a platform engineering role with substantial independent responsibility for CI pipelines, reproducible packaging, deterministic installation, release engineering, runtime hardening, observability, and software supply‑chain integrity. The role is designed to be primarily engineering and platform‑development work, not routine support, and it directly impacts software delivery and platform reliability across a globally distributed scientific infrastructure.

This is an engineering‑heavy role – expect 90%+ project/building time vs break‑fix.

• Design and implement CI pipelines for scientific software across macOS and Linux.
• Develop regression and smoke test harnesses for packaged software.
• Catch failures before distribution rather than after client installation.
• Support fast‑moving development branches (e.g., nightly builds) safely.

• Help define and enforce a canonical build contract.
• Improve dependency tracking and version control.
• Enable deterministic rebuilds across environments.
• Contribute to artifact integrity and metadata tracking (e.g., SBOM readiness).

• Add tests and versioning discipline to SBGrid’s runtime wrapper system (“capsules”).
• Introduce feature flags and safer rollout mechanisms.
• Improve logging, observability, and error classification.
• Develop dashboards and structured signals around build failures and common error states.
• Reduce reliance on tribal knowledge by encoding workflows into systems.

Core platforms

• Linux (expert‑level): shells, process model, file systems, tool chains, debugging, perf basics
• macOS (strong): building, testing, and release workflows across Intel + Apple Silicon

• CI/CD:
  Git Lab CI (or equivalent CI systems and concepts)
• Scripting and automation:
  Bash + Python (primary)
• Performance‑oriented implementation as needed:
  Go and/or Rust (selectively, for the hot paths)

• Current + future packaging direction: evaluating/adopting Nix/Spack/Homebrew‑style approaches
• Dependency management, artifact metadata, caching, provenance, reproducible builds Execution environments
• Containers and virtualization:
  Docker/Podman, VMs, and orchestration concepts (framework‑agnostic; Kubernetes/Open Shift not required)
• (Nice‑to‑have) Apptainer/Singularity in scientific/HPC contexts

• Git, code review workflows, testing discipline, documentation‑first habits

• Research/HPC exposure (Slurm, shared file systems, scientific software stacks)
• AWS familiarity (useful, not required)

• Minimum of five years’ post‑secondary education or relevant work experience.