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# Bioinformatics Software Engineer

- **Company:** Harvard University
- **Location:** Boston, MA, United States
- **Contract:** Temporary to permanent
- **Skills:** Amazon Web Services, Amazon Elastic Compute Cloud, Amazon S3, Data Analysis, Automation of Tests, Bioinformatics, Cloud Computing, Computational Biology, Computer Programming, Continuous Integration, Data as a Services, Data Integrity, Linux, Distributed Systems, Python (Programming Language), Meta-Data Management, Shell Script, Software Engineering, Workflow Management Systems, Cloud Platform System, High Performance Computing, Delivery Pipeline, Git, Containerization, Deployment Automation, Software Version Control, Docker
- **Published:** November 5, 2026
- **Apply:** https://www.careerbuilder.com/job-details/bioinformatics-software-engineer-boston-ma--dfa6e2a5-b592-4547-8b21-c18ffd22f610

## About the Role

Bioinformatics, Software Engineering, Team Player, Leadership, Scholarship, Training/Teaching, Medicine, Human Health, Biomedicine, Software Development, * Minimum of five years' post-secondary education or relevant work experience., * 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.

## Description

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., 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/PacBio/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: https://github.com/smaht-dac/main-pipelines.

 * 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.