Informatics Engineer

Prime Medicine•Cambridge, MA

1d•$134,000 - $163,000•Hybrid

About The Position

Prime Medicine is seeking an Informatics Engineer to construct the scientific data and computing platform essential for their gene editing programs. This role involves close collaboration with computational biology and cloud infrastructure teams. The ideal candidate will be comfortable managing a platform from end-to-end, establishing the engineering foundations for scientific data, including data pipelines and APIs, and developing AI-enabled internal tools. The engineer's judgment will significantly influence how Prime Medicine handles scientific data on a daily basis.

Requirements

5+ years of full-time engineering experience (3+ for those with an MS or PhD) in production environments.
Strong Python programming skills.
Production AWS experience with expertise in event-driven, cloud-native architectures, including AWS Lambda, EventBridge (or comparable event-routing infrastructure), and Infrastructure as Code with Terraform or CDK.
Experience with Docker/containerization, Git-based workflows, CI/CD, code review, and testing code in DEV/TEST environments before deploying to production.
A proven track record of building integrations and automations.
Experience in a life-science related industry involving scientific or regulated data, such as biotech, pharma, healthtech, clinical informatics, scientific instrumentation, or agricultural genomics.

Nice To Haves

NGS expertise. Knowledge of NGS technology, workflows and pipeline architecture is strongly preferred.
Hands-on workflow orchestration experience. Familiarity with Nextflow/NextFlow Tower/Seqera Platform preferred.
Laboratory informatics experience with Benchling or comparable ELN/LIMS, as an operator, builder, or administrator.
AI / LLM tooling and agentic systems (LangChain, LangGraph, MCPs, RAG architectures).
Gene editing familiarity: CRISPR, base editing, prime editing.
GxP / 21 CFR Part 11 / regulated-software experience.
Plotly Dash, Streamlit, Spotfire, Retool, or similar tools for internal apps and data visualizations.
Experience managing or querying relational databases (PostgreSQL, MSSQL).

Responsibilities

Design and build the data platform connecting NGS instruments, laboratory informatics systems (Benchling), and AWS cloud compute, encompassing automated ingestion, provenance tracking, scalable storage, and observability.
Build production-grade APIs, SDKs, and internal tools to provide scientists across the organization with access to genomic data and analytical capabilities.
Construct the orchestration layer for automated, event-triggered execution of scientific pipelines, taking ownership of their execution, scaling, and integration.
Implement AI-powered and agentic capabilities, such as RAG over internal scientific data, agentic workflows with human-in-the-loop review, and internal copilots to streamline routine workflows across science and business needs.
Develop integrations across the scientific tool chain to ensure reliable data movement between ELNs, LIMS, instrument software, and cloud compute.
Translate scientific requirements into reliable, maintainable software, transitioning research prototypes into production-grade systems.
Collaborate with computational biologists, lab scientists, and the cloud-support team to continuously enhance platform performance, cost-efficiency, and reliability.