APHEASARC Scientific Cloud Platform Developer

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AP107 HEASARC Scientific Cloud Platform Developer

Greenbelt, MD

AP107

1

The High‑Energy Astrophysics Software Archive (HEASARC) at NASA's Goddard Space Flight Center (GSFC) seeks an experienced scientific systems developer/cloud engineer to fill a gap in our team. The first task is to develop and test ways of migrating some services to AWS, i.e., deploying complex, software‑ and CPU‑heavy services on the cloud. The exploration includes both technical feasibility (software containerization, cloud data access, optimization, etc.)

as well as cost. The second task is to support the Fornax science platform, which deploys a Jupyter stack on AWS. The HEASARC is responsible for the user’s containerized software environment on this platform. This task includes developing and deploying Jupyter Lab extensions, installing 3rd‑party software, debugging existing interfaces, and solving issues that arise within the container or between the container and the AWS infrastructure (in collaboration with the cloud engineering team).

• Hands‑on experience with software containerization (Docker, Kubernetes or equivalent) in a production or research computing environment
• Python and Bash scripting in Unix environments
• Practical AWS experience; compute, storage, and networking services (EC2, S3, EFS, or similar)
• Ability to evaluate technical feasibility and document trade‑offs clearly for both engineering and program stakeholders
• Experience diagnosing problems that span application software, container configuration, and cloud infrastructure
• Strong version control and configuration management practices (Git)
• US Citizenship or Permanent Residency (LPR) required, with US residency for the past 3 consecutive years.
• Ability to obtain and maintain a Tier 1 Investigation through NASA.

• Familiarity with HEASARC tools or high‑energy astrophysics data formats (HEASoft, FTOOLS, XSPEC, FITS)
• Experience developing or maintaining scientific data software or pipelines
• Background in research software engineering or scientific computing
• Familiarity with cloud cost modeling and optimization strategies