Software Engineer, Agents

About the role

The Role Output has built a biological reasoning model that understands biology at the scale and complexity life actually operates. Our model independently learned the principles of molecular interactions, opening up drug treatments that were previously impossible. We're already generating therapies that traditional approaches cannot reach. The hardest problems in both AI and biology are being solved here, and there is room for you to own one.

Responsibilities

• Build the agent infrastructure that turns model capabilities into usable tools and workflows
• Owning the orchestration layer, the inference serving, the internal tooling, and the interfaces that researchers and external systems interact with
• Design and build the agent orchestration system that composes model capabilities into multi-step workflows, handling sequencing, state management, and error recovery
• Implement agent skills and tools that expose model capabilities to automated and interactive workflows
• Build inference infrastructure for serving models efficiently, optimizing for latency, throughput, and reliability
• Design and build APIs and integrations, including MCP-compatible interfaces, that allow external systems and users to interact with Output's models
• Build internal tools that accelerate the research team's work, from experiment management to evaluation pipelines
• Establish and maintain software engineering practices across the team: testing, CI/CD, code review, and documentation

Requirements

• A BS in Computer Science or a related field, or equivalent experience
• 4+ years of experience building production software systems
• Experience integrating ML models into products or workflows, including LLM-based systems
• Strong Python engineering skills with a track record of building maintainable, well-tested production code
• Experience designing APIs and building systems that other engineers and researchers depend on
• Experience with cloud infrastructure, containerization, and deployment pipelines
• Comfortable with systems design: you design for reliability, observability, and graceful failure, not just the happy path

Qualifications

• Bonus points for experience with LLM orchestration frameworks, agent architectures, or tool-use patterns
• Bonus points for experience with MCP (Model Context Protocol) or similar model-integration protocols
• Bonus points for a background in biology, chemistry, computational biology, or a related natural science
• Bonus points for experience building internal tools that accelerate research or data science teams
• Bonus points for experience with inference optimization for large models

Skills

• Python engineering skills
• Cloud infrastructure
• Containerization
• Deployment pipelines
• API design and building
• Internal tool development
• Inference optimization

Benefits

• Healthy feedback focused environment
• Competitive salary and equity in a growing, well-funded startup
• Excellent medical, dental, and vision coverage

Pay

• Competitive salary and equity in a growing, well-funded startup

Schedule

• Full-time