Senior Software Engineer, Lab Software
About the role
Join us in shaping the future of science! We are seeking Senior Software Engineers with backend experience to join our Lab Software Team (LaS).
What You'll Be Building
- Design & Build UI and APIs: High-performance, secure, and well-documented UI and APIs that integrate with AI-driven applications.
- Database Architecture & Scaling: Develop schemas and manage diverse data systems (SQL, NoSQL, Vector DBs, and others) for optimal performance and scalability.
- Application Development: Drive the implementation of front-end and backend services, focusing on performance, maintainability, and reliability.
- Performance & Reliability: Diagnose and optimize system bottlenecks, ensuring high availability and low-latency performance across large-scale workloads.
- Cloud & Infrastructure: Leverage AWS services, Kubernetes, and modern DevOps practices to build and deploy production-grade systems at scale.
- Cross-Functional Collaboration: Work with ML researchers, engineers, and scientists to integrate data pipelines, APIs, and cloud infrastructure into scientific workflows.
What You'll Need To Succeed
- Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
- 5-8+ years of engineering experience building and deploying large-scale systems in production.
- Experience developing web apps across the full stack (React, TypeScript, TailWind, FastAPI, SQL/NoSQL, Python, Pydantic).
- Hands on experience using AI coding assistants to drive productivity.
- Communication & Collaboration: Acute listening skills, and a proven track record of working cross-functionally with scientists, data engineers, and product teams; able to explain complex ideas to diverse audiences.
- Problem Solving: Proven ability to take ownership of complex backend challenges, balancing trade-offs between scalability, performance, and maintainability.
Bonus Points For
- Domain Background: Exposure to laboratory software for life sciences, material sciences, or related fields.
- Laboratory Automation Experience: Experience with laboratory devices, robotics, or hardware drivers.
- Orchestration Systems: Experience with software orchestration platforms (Airflow, Prefect, Temporal, Dagster) and design patterns.
- Cloud & DevOps Knowledge: Hands-on experience with AWS; strong understanding of Kubernetes and containerization, infrastructure-as-code (Terraform, CloudFormation), and CI/CD pipelines (GitHub Actions).
Compensation
We offer competitive base compensation with bonus potential and generous early-stage equity. Your final offer will reflect your background, expertise, and expected impact.
About LILA
Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges. We believe science is the most inspiring frontier for AI. Rather than hard-coding expert knowledge into tools, LILA builds systems that can learn for themselves. LILA combines advanced AI models with proprietary AI Science Factory™ instruments into an operating system for science that executes the entire scientific method autonomously, accelerating discovery at unprecedented speed, scale, and impact across medicine, materials, and energy.