About the RoleXaira is pioneering an AI-native approach to discovering and developing the next generation of life-changing medicines. We are building predictive and agentic AI systems across drug discovery, and the X-Scientist team accelerates this mission by making AI-assisted science reliable, usable, and scalable across drug discovery workflows.
On the X-Scientist team, you will work at the intersection of AI, software engineering, and therapeutic discovery. You will collaborate closely with AI scientists, engineers, platform teams, and drug discovery experts to build systems that connect AI models, biological tools, datasets, and scientific workflows.
This role spans backend systems, APIs, tool-calling infrastructure, workflow orchestration, developer-facing SDKs and CLIs, and agentic interfaces that help scientists run analyses, inspect intermediate steps, and iterate on results.
What You'll Do- 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.
What We're Looking For- 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.
Nice to Have- 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.
CompensationWe offer a competitive compensation and benefits package, including base salary, bonus, and equity. The base pay range for this position is expected to be $140,000 - $215,000 annually; however, the base pay offered may vary depending on market, job-related knowledge, skills and capabilities, and experience.
