Software Engineer, X-Scientist

Backend systems and APIs that connect AI models to scientific tools, datasets, and analysis workflows

Tool-calling infrastructure, CLIs, SDKs, and workflow runners that scientists and ML researchers use day-to-day

Agentic interfaces where users can run analyses, inspect intermediate steps, and iterate on results

Observability and testing for long-running workflows that call external tools and produce scientific outputs

Design reliable systems for long-running, multi-step workflows with strong testing, observability, logging, and maintainability.

Collaborate with scientific and technical teams to turn complex research workflows into usable, extensible software.

Strong Python engineering fundamentals, with clean, typed, tested, maintainable code.

Experience building at least one of the following: a production library, CLI, API, SDK, backend service, workflow system, or developer platform.

Familiarity with LLM application development, agent frameworks, tool calling, MCP-style interfaces, or orchestration systems.

Comfort working with complex systems that combine multiple components, external calls, domain-specific logic, and evolving user needs.

Good instincts for abstraction, error handling, reliability, and designing software that can grow across use cases.

Strong communication skills and ability to work in a collaborative, multidisciplinary environment.

Background or interest in computational biology, bioinformatics, protein design, single-cell genomics, biomedical AI, or adjacent domains.

Familiarity with biomedical databases or tools such as PubMed, UniProt, AlphaFold, PDB, DepMap, or related resources.

Curiosity about biology and scientific research; you do not need a biology background, but you should be excited to learn the domain and work closely with scientists and ML researchers.