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 Description

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/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.

Job Description: 

• 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.

 

Qualifications

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.

Additional Information

• 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 support the position. 
• Standard Hours/Schedule: 35 hours per week
• Visa Sponsorship Information: Harvard University is unable to provide visa sponsorship for this position.
• Pre-Employment Screening: Identity
• Other Information: Please note that we are currently conducting a majority of interviews and onboarding remotely and virtually. We appreciate your understanding.
• Staying Informed About Your Application: Due to the high volume of applications, we may not always be able to reach out right away, but you can track your status anytime through the Careers@Harvard portal.

#LI-DK1

Work Format Details

This position has been determined by school or unit leaders that some of the duties and responsibilities can be effectively performed at a non-Harvard location. The work schedule and location will be set by the department at its discretion and based upon operational needs. When not working at a Harvard or Harvard-designated location, employees in hybrid positions must work in a Harvard registered state in compliance with the University’s Policy on Employment Outside of Massachusetts. Additional details will be discussed during the interview process. Certain visa types and funding sources may limit work location. Individuals must meet work location sponsorship requirements prior to employment.

Salary Grade and Ranges

This position is salary grade level 057. Please visit  Harvard's Salary Ranges  to view the corresponding salary range and related information. 

Benefits

Harvard offers a comprehensive benefits package that is designed to support a healthy work-life balance and your physical, mental and financial wellbeing. Because here, you are what matters. Our benefits include, but are not limited to: 

• Generous paid time off including parental leave 
• Medical, dental, and vision health insurance coverage starting on day one 
• Retirement plans with university contributions 
• Wellbeing and mental health resources 
• Support for families and caregivers 
• Professional development opportunities including tuition assistance and reimbursement 
• Commuter benefits, discounts and campus perks 

Learn more about these and additional benefits on our Benefits & Wellbeing Page. 

EEO/Non-Discrimination Commitment Statement

Harvard University is committed to equal opportunity and non-discrimination. We seek talent from all parts of society and the world, and we strive to ensure everyone at Harvard thrives. Our differences help our community advance Harvard's academic purposes.

Harvard has an equal employment opportunity policy that outlines our commitment to prohibiting discrimination on the basis of race, ethnicity, color, national origin, sex, sexual orientation, gender identity, veteran status, religion, disability, or any other characteristic protected by law or identified in the university's non-discrimination policy. Harvard's equal employment opportunity policy and non-discrimination policy help all community members participate fully in work and campus life free from harassment and discrimination.