FL103 | Cambridge, MA Engineer, Software Engineering

Pioneering Medicines; Cambridge (MA); On-site; USD 74,000 - 127,000; Full time

Benefits offered by this job

Healthcare coverage

Annual incentive program

Retirement benefits

Job summary

Flagship Pioneering is seeking an Engineer, Software Development to help design and evolve a biological research platform that turns experimental work into organized, analysis-ready data. You’ll own the design through operation, preserving sample lineage and experimental context while building reliable computational workflows.

You will collaborate with experimental teams, design schemas, and orchestrate pipelines that harmonize heterogeneous data, enabling powerful querying, AI-enabled

Qualifications

• 3+ years post M.S. in CS; biology exposure preferred
• Hands-on programming and AI workflow orchestration with ability to specify architecture and constraints
• Data modelling with relational models, ORMs, and impact on queries (PostgreSQL on AWS)
• Python data engineering with Pandas, NumPy, and PyArrow
• Integration and automation experience (FastAPI, REST, Benchling) and AWS credentials/permissions
• Strong data integrity focus; prioritizes reliable, testable results over individual components
• Biological knowledge preferred (genes/proteins, assays, transcriptomics) and collaboration with scientists

Responsibilities

• Learn how experiments are run and how samples/results are tracked to remove slow manual steps
• Design reusable data models and workflows from concept through testing and operation
• Create schemas/interfaces spanning computational inputs/outputs to experimental records
• Build or orchestrate pipelines to harmonize metadata and validate results across systems
• Make data accessible via APIs, visualizations, and AI-enabled interfaces
• Configure safe cloud infrastructure and distinguish testing vs. deployment
• Preserve provenance, units, controls, QC; write meaningful tests and guard against bad joins
• Work with scientists on metadata conventions and workflows that fit lab practices

Skills

Programming experience

AI workflow orchestration

Data modelling

Python data engineering

AWS knowledge

Data integrity

Biology knowledge

Education

M.S. in Computer Science

Tools

PostgreSQL on AWS RDS

SQLAlchemy

Alembic

NumPy

Pandas

PyArrow

REST

Benchling

FastAPI

Bedrock

Job description

What if… you could help build a research platform that turns experimental biology into organized, accessible, analysis-ready data?

Experimental work generates data across many files, records, and systems, and manual handling of samples and results slows progress. A reliable computational platform can preserve sample lineage and experimental context and make data available through APIs, visualizations, and AI-enabled interfaces, so scientists can easily find, compare, and act on in-house data alongside the literature and other advances in the field.

FL103 is seeking an Engineer, Software Development to help design and evolve our biological research platform. The successful candidate will work with the computational modeling and experimental teams to learn how computational outputs become experimental inputs, how results return, and where manual handling slows progress. They will then move as much of that handling as practical onto reliable computational workflows that are transparent and easy to query.

FL103 was founded by Flagship Pioneering, an innovation enterprise dedicated to originating and developing companies that invent breakthrough technologies to transform health care, agriculture, and sustainability. Since Flagship's founding in 2000, the firm has originated and fostered more than 100 scientific ventures, including Moderna Therapeutics, Generate Biomedicines, and Indigo Agriculture.

Position Summary:

The successful candidate will help design and evolve a biological research platform that turns experimental work into organized, accessible, analysis-ready data. This is a platform and automation role, not a series of isolated programming tasks: the work is owned from design through operation, and the result should preserve sample lineage and experimental context.

Responsibilities:

• Learn how experiments are run and how samples and results are tracked, and identify where manual handling slows progress.
• Identify recurring needs, design reusable data models and workflows, and carry them through implementation, testing, and operation.
• Design schemas and interfaces spanning computational screening inputs and outputs through final experimental records, connecting compute and experimental work and enabling powerful querying.
• Build or orchestrate pipelines that parse heterogeneous files and records, harmonize metadata, validate results, and load shared systems, replacing repetitive manual steps with recoverable workflows across laboratory records, cloud storage, databases, and external services.
• Make data available through APIs, visualizations, and AI-enabled interfaces.
• Configure and operate shared cloud infrastructure safely, distinguishing between testing a change and applying it.
• Preserve provenance, units, controls, and QC; write meaningful tests; and catch bad joins or transformations, including in generated code.
• Work directly with experimental scientists on metadata conventions, ambiguous records, and workflows that fit how the lab works, so the team can easily find, compare, and act on in-house data alongside the literature and other advances in the field.

Qualifications:

• 3+ Years of experience post M.S., preferably in Computer Science, exposure to biology preferable
• Hands‑on programming, effective orchestration of AI coding agents, or both, with the ability to specify architecture and constraints, validate what is built, and take responsibility for the result
• Data modelling skills, including relational models and ORMs, sample and experiment identity, and how modelling choices affect later queries (current stack: PostgreSQL on AWS RDS, SQLAlchemy, and Alembic)
• Python data engineering experience (Pandas, NumPy, and PyArrow are useful)
• Integration and automation experience (current stack: FastAPI, Benchling, REST, and MCP)
• Working knowledge of AWS (S3, RDS, EC2, Secrets Manager, and Bedrock), including credentials and permissions
• Strong judgement on data integrity. Demonstrated delivery matters more than any particular tool, or than having written every component by hand
• Biological knowledge strongly preferred (genes and proteins, cell types, antibody assays, transcriptomics, proteomics, controls, and replicates), and comfort collaborating with experimental scientists

Helpful, but not required:

• Laboratory automation: connecting instruments or control systems to software and AWS. The role may later extend from data handling into experimental automation.
• LLM applications: structured extraction, evidence checks, evaluation, and cost control with Bedrock, Anthropic, or OpenAI.
• Interfaces: React/TypeScript, Vite, and Plotly.
• Familiarity with relational databases

Flagship Pioneering is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, genderidentityor Veteran status.

Recruitment & Staffing Agencies

Flagship Pioneering and its affiliated Flagship Lab companies (collectively, "FSP") do not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to FSP or its employees is strictly prohibited unless contacted directly by Flagship Pioneering's internal Talent Acquisition team. Any resumes submitted by an agency in the absence of a signed agreement will automatically become the property of FSP, and FSP will not owe any referral or other fees with respect thereto.

The salary range for this role is $74,000 - $126,500. Compensation for the role will depend on a number of factors, including a candidate's qualifications, skills, competencies, and experience. FL103 currently offers healthcare coverage, annual incentive program, retirement benefits and a broad range of other benefits. Compensation and benefits information is based on FL103's good faith estimate as of the date of publication and may be modified in the future.