Compute Platform Engineer I

Role Summary

A Compute Platform Engineer I is a technical contributor who translates poorly defined business or technical problems into well-defined specifications and executes on them with a focus on measurable impact and reliable operations. They model best practices for software development, including code quality, documentation, DevOps, and testing, and serve as an escalation point for the operation of existing services, pipelines, and workflows. The role involves engaging with customers and the open-source community, contributing to pull requests when appropriate. Location: multiple site locations across Cambridge, MA; Seattle, WA; South San Francisco, CA; and Upper Providence, PA.

Responsibilities

• Designs, builds, and operates tools, services, workflows, etc., that deliver high value through the solution to key business problems.
• Responsible for development of key components of a hybrid on-prem/cloud compute platform for interactive and scalable batch computing and establishing processes/workflows to transition existing HPC users and teams to this platform.
• Responsible for code-driven environments, applications, and container/image builds as well as CI/CD-driven application deployments.
• Consults science users on application scalability to PBs of data by applying deep understanding of software engineering, algorithms, and underlying hardware infrastructure and their impact on performance.
• Confidently optimizes design and execution of complex solutions within large-scale distributed computing environments.
• Produces well-engineered software, including automated test suites, technical documentation, and operational strategy.
• Ensures consistent application of platform abstractions to maintain quality and consistency with respect to logging and lineage.
• Fully versed in coding best practices, participates in code reviews, and helps improve the team’s standards.
• Adheres to QMS framework and CI/CD best practices and helps guide improvements to them that improve ways of working.

Qualifications

• Required: Bachelor's degree in Data Engineering, Computer Science, Software Engineering or related field.
• Required: Experience in programming languages such as Python, Go, C++, Scala, Java, including toolchains for documentation, testing, and operations/observability.
• Required: Experience with modern software development tools and practices (e.g., Git/GitHub, DevOps tools, metrics/monitoring).
• Required: Cloud experience (e.g., AWS, Google Cloud, Azure), including infrastructure-as-code tools and scalable compute technologies (e.g., Google Batch and Vertex).
• Required: Experience with CI/CD implementations using Git and a common CI/CD stack (e.g., Azure DevOps, CloudBuild, Jenkins, CircleCI, GitLab).
• Required: Experience in Linux/Unix.
• Preferred: Experience with Docker, Kubernetes, and the CNCF ecosystem, including deployment tools such as Helm.
• Preferred: Experience with low-level build tools (Make, CMake) and automated build systems such as Spack or EasyBuild.
• Preferred: Experience in CI/CD implementations using Git and a common CI/CD stack (e.g., Jenkins, CircleCI, GitLab, Azure DevOps).
• Preferred: Experience in workflow orchestration with Argo Workflow, Airflow, and scientific workflow tools such as Nextflow, Snakemake, VisTrails, or Cromwell.
• Preferred: Experience with application performance tuning and optimization in parallel and distributed computing, including MPI, OpenMP, Gloo, and understanding of hardware, networks, and storage.
• Preferred: Experience with agile software development environments using Jira and Confluence.
• Preferred: Familiarity with high-performance applications and open-source community contributions.