Engineer Jobs

About The Position

Requirements

• Bachelor’s or Master’s degree in computer science, software engineering, bioinformatics, or a related coding-heavy major.
• At least 5 years of work experience within the biology domain.
• Proven experience building or operating production data systems or pipelines in bioinformatics, data engineering, platform/SRE, or ML infrastructure, including Postgres and S3-backed data storage.
• Hands-on experience with containers such as Docker or Podman and cloud infrastructure; infrastructure as code is preferred, with AWS services including ECS Fargate, EC2, S3, EFS, Step Functions, IAM, VPC, and CDK cited.
• Exposure to workflow/orchestration tools such as Step Functions and Nextflow or Snakemake, and to event-driven patterns.
• Ability to partner with ML/Computational Biology and Lab Platform users.
• Clear written and verbal communication with non-engineers, and product/UX instincts for scientific users; FastAPI and React/TypeScript are cited.
• Intellectual curiosity, scientific rigor, and enthusiasm for working in a fast-paced, evolving research environment.

Nice To Haves

• Bioinformatics breadth spanning sequencing, mass spectrometry, and imaging, including NGS formats such as FASTQ and BAM/CRAM and pipeline experience with Cell Ranger, RNA-seq tooling, or HLA typing.
• Familiarity with protein language models, protein structure prediction, and molecular dynamics simulation.
• Experience with SSO/OAuth integration and observability tooling such as CloudWatch.
• Exposure to SOC2, ISO27001, or GxP.
• Agentic coding fluency: ability to structure and direct AI coding tools effectively.
• Exposure to enabling ML scientists through artifact stores/registries and dataset versioning.

Responsibilities

• Build and operate bioinformatics pipelines from instrument to data ecosystem using workflow orchestration and containerized execution.
• Build durable data platforms that support data discovery by exposing data through clean, well-documented internal APIs, applications, and SQL databases.
• Provision and manage cloud infrastructure as code using secure engineering practices to keep systems robust, safe, and maintainable.
• Own engineering standards for the team, including CI/CD test automation, version control, and design and review practices that support maintainability as the team grows.
• Lead incident reviews and preventative improvements to diagnose root causes of failures and build safeguards that prevent recurrence with verifiable gating mechanisms.
• Own end-to-end data processing and delivery to support scientific decision-making across the organization.
• Develop agentic workflows and harnesses for developing bioinformatics pipelines.

Benefits

• Medical insurance
• Dental insurance
• Vision insurance
• Life insurance
• Flexible time off
• 401(k)-retirement plan
• Short- and long-term incentive opportunities