Senior Software Engineer, App
AI summary of the role
Senior Software Engineer on the Application Team building the AI-native platform that integrates ML, life sciences, physical sciences, and software into a seamless experience for researchers.
No longer in the current catalog. Last included 2026-09-09. Check the employer’s posting for availability.
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) for optimal performance and scalability
- Drive 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
What you’ll bring
- 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, strong in backend
- Full stack development experience with React, TypeScript, Monorepos (Nx), TailWind, FastAPI, SQL/NoSQL, Python, Pydantic
- Hands-on experience using AI coding assistants to drive productivity
Technologies
React · TypeScript · Nx · TailWind · FastAPI · Python · Pydantic · SQL · NoSQL · Vector DBs · AWS · Kubernetes
About Lila Sciences
Autonomous AI platform that executes the scientific method end-to-end—from hypothesis generation to experimental execution—for biotech, materials, and chemical R&D.
Series A
Source and classification
Internal deployment & tooling · Evidence for this classification:
Your Impact at LILA Scientists 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. About The Team The Application Team sits at the center of LILA — the integration point where Machine Learning, Life Sciences, Physical Sciences, and Software become one AI-native experience that carries a scientist from hypothesis to experiment to breakthrough results. AI isn't a feature here — it's the architecture. Agent frameworks, tools, and LLM orchestration are core primitives, not bolt-ons. The problems are genuinely hard. Connecting AI to automated lab
More from the job description
Your Impact at LILA Scientists 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. About The Team The Application Team sits at the center of LILA — the integration point where Machine Learning, Life Sciences, Physical Sciences, and Software become one AI-native experience that carries a scientist from hypothesis to experiment to breakthrough results. AI isn't a feature here — it's the architecture. Agent frameworks, tools, and LLM orchestration are core primitives, not bolt-ons. The problems are genuinely hard. Connecting AI to automated lab workflows, ML pipelines, and multi-domain knowledge graphs means inventing patterns, not copying them. You'll learn domains you never expected. Working shoulder-to-shoulder with lab scientists and ML engineers means your technical surface area grows fast. You'll ship things that matter. The tools you build accelerate research timelines from months to days. If you want to build at the intersection of AI and science, move fast without breaking trust, and grow into the kind of engineer who can architect [... source excerpt omitted ...] h 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 t
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