Software Engineer - X-Scientist

4w1 month ago

Xaira Therapeutics

South San Francisco, US · Full-time · $140,000 – $215,000

About this role

Xaira is an innovative biotech startup leveraging AI to transform drug discovery and development. As a Software Engineer on the X-Scientist team, you will work at the intersection of AI, software engineering, and therapeutic discovery, building systems that connect AI models to biological tools and scientific workflows.

Your day-to-day work 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. You will also ensure observability and testing for long-running workflows that call external tools and produce scientific outputs.

You will collaborate closely with AI scientists, ML researchers, platform teams, and drug discovery experts. The multidisciplinary environment combines deep technical work with scientific curiosity, requiring you to turn complex research workflows into usable, extensible software. This role offers the chance to shape foundational infrastructure for AI-driven drug development.

The X-Scientist team accelerates the mission of making AI-assisted science reliable, usable, and scalable across drug discovery workflows. By building the underlying systems, you directly enable the identification of novel therapies and improve success in drug development.

Requirements

Strong Python engineering fundamentals, with clean, typed, tested, maintainable code.
Experience building at least one of: 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.

Responsibilities

Build backend systems and APIs that connect AI models to scientific tools, datasets, and analysis workflows.
Develop tool-calling infrastructure, CLIs, SDKs, and workflow runners that scientists and ML researchers use day-to-day.
Create agentic interfaces where users can run analyses, inspect intermediate steps, and iterate on results.
Implement 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.