Staff Software Engineer, Lab Software

Lila Sciences Lila Sciences · AI Frontier · Alewife, Cambridge, MA · Software

Staff Software Engineer role focused on building the physical and virtual execution layer for Lila's AI-driven science, connecting AI models to experimental instruments. This involves designing and building UIs and APIs, managing diverse data systems (including Vector DBs), developing backend services, optimizing performance, and leveraging cloud infrastructure (AWS, Kubernetes). The role requires strong backend experience and collaboration with ML researchers and scientists.

What you'd actually do

  1. Design & Build UI and APIs: Design and build high-performance, secure, and well-documented UI and APIs that integrate with AI-driven applications.
  2. Database Architecture & Scaling: Develop schemas and manage diverse data systems (SQL, NoSQL, Vector DBs, and others) for optimal performance and scalability.
  3. Application Development: Drive the implementation of front-end and backend services, focusing on performance, maintainability, and reliability.
  4. Performance & Reliability: Diagnose and optimize system bottlenecks, ensuring high availability and low-latency performance across large-scale workloads.
  5. Cloud & Infrastructure: Leverage AWS services, Kubernetes and modern DevOps practices to build and deploy production-grade systems at scale.

Skills

Required

  • 8+ years of engineering experience building and deploying large-scale systems in production
  • Strong backend development
  • Full Stack Development (React, TypeScript, TailWind, FastAPI, SQL/NoSQL, Python, Pydantic)
  • Hands on experience using AI coding assistants to drive productivity
  • Communication & Collaboration
  • Problem Solving

Nice to have

  • Domain Background in laboratory software for life sciences, material sciences, or related fields
  • Lab Automation Experience
  • Orchestration Systems (Airflow, Prefect, Temporal, Dagster)
  • Cloud & DevOps Knowledge (AWS, Kubernetes, Terraform, CloudFormation, GitHub Actions)

What the JD emphasized

  • Staff Software Engineers with backend experience
  • You must be strong in backend
  • Hands on experience using AI coding assistants to drive productivity is required.

Other signals

  • AI-driven science
  • AI Science Factories
  • orchestration of labflows
  • integrate data pipelines, APIs, and cloud infrastructure into scientific workflows