Senior Software Engineer

Formation Bio•Boston, MA

8d•$185,500 - $232,000•Hybrid

About The Position

As a Senior Software Engineer at Formation Bio, you will build high-leverage software across the organization. You will turn ambiguous problems into products and systems that help people, applications, AI Enabled Employees, and Agents make better decisions and move faster. This is an AI-native engineering role. You use modern AI and agentic development tools as a core part of how you explore, build, test, and operate software. You will also help create software that incorporates AI responsibly, with the interfaces, data access, evaluation, and operational controls needed to make these systems useful in practice. Our products and priorities evolve quickly as we learn. You will be expected to make progress with incomplete information, identify the highest-value path forward, communicate tradeoffs clearly, and reorient quickly when new information changes the priority. This role has a backend and systems center of gravity. We value full-stack range, with a primary focus on backend, systems, product, and AI engineering.

Requirements

5+ years of experience building and shipping production software, or equivalent senior-level experience.
Strong backend and systems engineering fundamentals, including APIs, distributed systems, databases, cloud services, and asynchronous workflows.
Daily experience using AI tools, LLMs, or agentic development systems as part of the engineering workflow.
Experience operating production software with appropriate testing, observability, security, and follow-through after launch.
Exceptional communication and collaboration skills across Product Engineering, Data Engineering, Data Science, SRE, and non-technical partners.

Nice To Haves

Experience in pharmaceutical, biology, and/or biotechnology software and data is a strong plus.
Experience building AI-enabled software, agentic workflows, retrieval systems, tool integrations, or other ML-powered products is a strong plus.
Familiarity with ML concepts such as training versus inference, embeddings, retrieval, evaluation, data quality, and model limitations is a plus. Deep ML research experience is not required.
Strong product judgment and the ability to make progress with incomplete information, identify high-value problems, and adapt quickly as priorities change.
We value full-stack range, with a primary emphasis on backend, systems, product, and AI engineering.

Responsibilities

Own meaningful product or platform outcomes from problem definition through design, implementation, launch, and iteration.
Build and operate production services, APIs, integrations, databases, asynchronous workflows, and distributed systems.
Build software for people, applications, AI Enabled Employees, and Agents, including the tools, APIs, permissions, state, observability, and failure handling required for reliable use.
Design and ship AI-enabled and agentic workflows, including tool use, retrieval, data access, evaluation, and appropriate human review.
Use LLMs and agentic coding systems daily for exploration, prototyping, implementation, testing, debugging, documentation, and automation while maintaining a high bar for validation.
Partner with Data Engineering on application data models, data products, data contracts, and access patterns.
Partner with Data Science on ML-powered capabilities, model interfaces, evaluation, and production integration.
Partner with SRE on deployment, reliability, observability, security, and infrastructure decisions.
Make pragmatic tradeoffs between speed, quality, maintainability, and future flexibility. Use engineering rigor proportional to the risk and context of the system.
Reprioritize quickly as new information changes the highest-value path, and communicate decisions and tradeoffs clearly to technical and non-technical partners.
Review designs and code, mentor engineers, and raise the bar for product judgment and engineering quality.