Bioinformatics Software Engineer

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.

- 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.

- 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.

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

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• 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.

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.

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.