Bioinformatics Software 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.

Why join Harvard Medical School?

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.

Job Summary:

Participate in the design of software that supports and enriches research productivity and reliability; implement software solutions. Develop software and data services with researchers to ensure that modern standards of reproducible code are kept.

Job-Specific Responsibilities:

We are looking for a highly skilled Bioinformatics Software Engineer who specializes in designing, developing, deploying, and maintaining scalable bioinformatics pipelines on cloud-based infrastructure. The candidate will be responsible for the code base supporting the large-scale genomic processing and analysis pipelines at the SMaHT Data Analysis Center that manages multi-omic data (e.g., Illumina/Pac Bio/ONT Whole Genome Sequencing (WGS), RNA-Seq). The ideal candidate will have a deep understanding of next-generation sequencing (NGS) data analysis, workflow automation, cloud computing, and cloud software engineering best practices.

This role will support research and production environments where reproducibility, scalability, and performance are critical.

• Design, implement, and maintain bioinformatics pipelines for high-throughput sequencing data (e.g., alignment, QC, variant calling from WGS and RNA‑seq) similar to those in existing repositories:
• Build reproducible, well‑tested, and automated workflows using workflow management systems (particularly CWL).
• Architect and manage AWS‑based compute infrastructure to support pipeline execution, including automated deployment, scaling, and monitoring.
• Containerize workflows using Docker or similar tools for managed execution and portability.
• Integrate CI/CD tooling to automate testing, deployment, and version control to ensure data integrity and correct execution of the pipeline.
• Develop utility tools for metadata management, file integrity checks or conversion (e.g., VCF, BAM to CRAM), and integration with the SMaHT Data Portal.
• Collaborate cross‑functionally with research scientists, engineers, and IT teams to refine requirements and deliver high‑quality solutions.
• Document code, workflows, and infrastructure configurations clearly.

Basic Qualifications:

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

Additional

Qualifications and Skills:

• PhD in computational biology/bioinformatics/statistics/CS or another quantitative field is strongly preferred.
• Superb programming skills, especially in Python and shell scripting, and communication skills are strongly preferred.
• Extensive experience with analysis of high‑throughput sequencing data and knowledge of bioinformatics tools for sequence alignment, variant calling, sequence data QC, etc.
• Proficiency in Docker for creating a reproducible execution environment and Workflow Description Language for orchestrating complex tasks.
• Strong understanding of AWS services (EC2, S3) or similar cloud platforms for compute and storage.
• Version Control & CI/CD:
  Git, automated testing, deployment workflows.
• Experience with Linux systems, HPC, and distributed computing environments.
• Knowledge of optimizing pipelines for large‑scale genomic projects.

• Appointment End Date:
  This is a one‑year term position from the date of hire, with the possibility of extension, contingent upon work performance and continued funding to…