Your Impact at LILAScientists shouldn't have to context-switch between a dozen tools to go from hypothesis to result. We're building the platform that makes this a reality - and we need engineers who want to solve problems no one has solved before.
We're hiring Sr Principal / Principal Software Engineers to design the agents, interfaces, and platform integrations that let researchers seamlessly collaborate with AI.
What You'll Be Building- Design & Build UI and APIs: Design and build 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. You must be strong in backend.
- Full Stack Development: Experience developing web apps across the full stack (React, TypeScript, Monorepos like Nx, TailWind, FastAPI, SQL/NoSQL, Python, Pydantic)
- Hands on experience using AI coding assistants to drive productivity is required.
- 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- Applied AI Engineering: Experience building with AI agents, graph-based workflows, tool-use protocols (MCP), RAG pipelines, or LLM orchestration frameworks.
- 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).
- Experience with ORMs: Experience with and web services for CRUD services (SQLModel, FastAPI, Django).
- Orchestration Systems: Experience with orchestrators tools (Airflow, Prefect, Temporal, Dagster).
- Familiarity with Python for Science: Familiarity with data science and ML libraries (pandas, numpy, scipy, jax, pytorch).
- Domain Background: Exposure to laboratory software or analytics for life sciences, material sciences, or related fields.
- Experience with laboratory devices, robotics, or hardware drivers.
CompensationWe offer competitive base compensation with bonus potential and generous early-stage equity. Your final offer will reflect your background, expertise, and expected impact.
U.S. Benefits. Full-time U.S. employees receive a comprehensive benefits program including medical, dental, and vision coverage; employer-paid life and disability insurance; flexible time off with generous company wide holidays; paid parental leave; an educational assistance program; commuter benefits, including bike share memberships for office based employees; and a company subsidized lunch program.
International Benefits. Full-time employees outside the U.S. receive a comprehensive benefits program tailored to their region. USD salary ranges apply only to U.S.-based positions; international salaries are set to local market.
Expected Base Salary Range
$144,000-$240,000 USD
