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Lila Sciences is building a scientific superintelligence platform and autonomous lab to solve humankind's greatest challenges in human health, climate, and sustainability by applying AI to the scientific method.

Requirements

• Expertise in Databases: Strong experience with SQL, NoSQL, and emerging database technologies (e.g., Vector DBs); proven track record in schema design, indexing, and query optimization.
• API Development: Proven ability to design and scale RESTful or GraphQL APIs with a focus on reliability and performance.
• Python Expertise: Strong experience with Python for backend services (e.g., FastAPI, Flask, Django).
• Cloud & DevOps Knowledge: Hands-on experience with AWS, GCP, or Azure; strong understanding of Kubernetes and containerization, infrastructure-as-code (Terraform, CloudFormation), and CI/CD pipelines (GitHub Actions).
• 4-8 years of backend engineering experience building and deploying large-scale systems in production.

Responsibilities

• Design & Build APIs: Design and build high-performance, secure, and well-documented APIs that integrate with AI-driven applications.
• Database Architecture & Scaling: Architect schemas and manage diverse data systems (SQL, NoSQL, Vector DBs, and others) for optimal performance and scalability.
• Backend Systems Development: Drive the implementation of 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.

Other

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
• 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.