AP107 HEASARC Scientific Cloud Platform Developer

Support•Greenbelt, MD

3d•Onsite

About The Position

The High-Energy Astrophysics Software Archive (HEASARC) at NASA's Goddard Space Flight Center (GSFC) seeks an experienced scientific systems developer/cloud engineer. The role involves developing and testing methods for migrating services to AWS, including deploying complex, software- and CPU-intensive services on the cloud. This exploration covers technical feasibility (software containerization, cloud data access, optimization) and cost analysis. Additionally, the position supports the Fornax science platform, which utilizes a Jupyter stack on AWS. The HEASARC is responsible for the user's containerized software environment on this platform. This includes developing and deploying JupyterLab extensions, installing third-party software, debugging existing interfaces, and resolving issues within the container or between the container and AWS infrastructure in collaboration with the cloud engineering team.

Requirements

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.

Nice To Haves

JupyterLab extension development or Jupyter deployment configuration experience
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

Responsibilities

Develop and test ways of migrating some services to AWS, deploying complex, software- and CPU-heavy services on the cloud.
Explore technical feasibility including software containerization, cloud data access, and optimization.
Analyze cloud deployment costs.
Support the Fornax science platform, which deploys a Jupyter stack on AWS.
Develop and deploy JupyterLab extensions.
Install 3rd party software.
Debug existing interfaces.
Solve issues that arise within the container or between the container and the AWS infrastructure (in collaboration with the cloud engineering team).