Senior Software Engineer, Lab Software

About the role

You will architect and deliver the backend systems that power Lila's AI-driven scientific workflows. You will own the design and implementation of high-performance APIs and user interfaces that connect AI science factories with physical laboratory instruments. You will collaborate daily with software engineers, lab scientists, and machine learning engineers to translate experimental requirements into robust software solutions. You will diagnose and resolve complex performance and reliability issues across large-scale, distributed lab environments. You will ensure that all development workflows adhere to best practices in git, testing, and user-centered design. You will play a key role in building the foundational infrastructure that turns AI hypotheses into validated scientific discoveries.

Key facts

What you'll do

• Design and build high-performance, secure, and well-documented UI and APIs that integrate with AI-driven applications.
• Develop schemas and manage diverse data systems (SQL, NoSQL, Vector DBs, and others) for optimal performance and scalability.
• Drive the implementation of front-end and backend services, focusing on performance, maintainability, and reliability.
• Diagnose and optimize system bottlenecks, ensuring high availability and low-latency performance across large-scale workloads.
• Leverage AWS services, Kubernetes and modern DevOps practices to build and deploy production-grade systems at scale.
• Work with ML researchers, engineers, and scientists to integrate data pipelines, APIs, and cloud infrastructure into scientific workflows.
• Implement reliable orchestration of labflows that coordinate experiments across real instruments and AI factories.
• Build bi-directional data transfer mechanisms that synchronize laboratory states with digital twins in real time.
• Create intuitive user experiences for AI scientists and operators to interact with complex laboratory systems.
• Maintain and evolve the Lila App to ensure seamless connectivity between software components and physical devices.
• Ensure all systems meet strict security, compliance, and audit requirements for scientific data handling.
• Contribute to technical documentation and knowledge sharing across cross-functional teams.

Requirements

• Hold a Bachelor's or Master's degree in Computer Science, Engineering, or related field.
• Bring 5-8+ years of engineering experience building and deploying large-scale systems in production with a strong backend focus.
• Demonstrate full stack development expertise with experience across React, TypeScript, TailWind, FastAPI, SQL/NoSQL, Python, and Pydantic.
• Prove hands-on experience using AI coding assistants to drive productivity in software development.
• Show acute listening skills and a proven track record of working cross-functionally with scientists, data engineers, and product teams.
• Exhibit the ability to explain complex technical ideas to diverse audiences without relying on jargon.
• Display strong ownership for solving complex backend challenges while balancing trade-offs between scalability, performance, and maintainability.
• Commit to working in a fast-paced environment where priorities can shift based on scientific discovery and experimental needs.
• Align with Lila's mission of transforming scientific research through advanced automation and AI.
• Thrive in a collaborative culture that values transparency, continuous learning, and extreme ownership of outcomes.
• Be located in or willing to relocate to Cambridge, MA USA for the duration of the role.
• Maintain eligibility to work in the United States without sponsorship for this position.

Nice to have

• Bring domain background in laboratory software for life sciences, material sciences, or related scientific fields.
• Offer experience with laboratory devices, robotics, or hardware drivers that interface with software systems.
• Demonstrate familiarity with orchestration systems such as Airflow, Prefect, Temporal, or Dagster and associated design patterns.
• Show hands-on experience with AWS services, strong understanding of Kubernetes and containerization, infrastructure-as-code tools like Terraform or CloudFormation, and CI/CD pipelines implemented with GitHub Actions.

Practical notes

This is a full-time role based in Cambridge, Massachusetts, requiring physical presence in the office. Travel requirements are minimal and tied to internal meetings or scientific site visits as needed. Candidates must be authorized to work in the United States without company sponsorship. The role is eligible to start as soon as the candidate completes onboarding and background checks.