Staff Software Engineer, SSR

Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges. They are seeking a Staff Software Engineer to join their Scientific System of Record Team to develop user interfaces, services, and high-performance APIs that integrate advanced AI frameworks with scientific analytics and workflows.

Responsibilities:

• User Interfaces and APIs: Design and build high-performance, secure, and well-documented UIs and APIs that integrate with AI-driven applications
• Database Architecture and Scaling: Develop schemas and manage diverse data systems, including SQL, NoSQL, vector databases, and other emerging technologies, for performance and scalability
• Application Development: Drive implementation of front-end and backend services with a focus on performance, maintainability, and reliability
• Performance and Reliability: Diagnose and resolve system bottlenecks while ensuring high availability and low-latency performance across large-scale workloads
• Cloud and 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

Requirements:

• Bachelor's or Master's degree in Computer Science, Engineering, or related field
• 6–8+ years of engineering experience building and deploying large-scale systems in production
• Strong expertise in at least one of the following areas, with the ability to work across the stack: front-end engineering, backend engineering, or data modeling and system design
• TypeScript, React, and Python: Strong experience with React and TypeScript is required; Python experience is strongly preferred
• Strong experience with SQL, NoSQL, and emerging database technologies such as vector databases; proven track record in schema design, indexing, and query optimization
• Proven ability to design and scale RESTful or GraphQL APIs with a focus on reliability and performance
• Hands-on experience using AI coding assistants to improve engineering productivity
• Experience working in life sciences, materials science, or other research-heavy or data-intensive fields
• Strong 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
• Proven ability to take ownership of complex technical challenges while balancing trade-offs between scalability, performance, and maintainability
• Hands-on experience with AWS, GCP, or Azure; strong understanding of Kubernetes, containerization, infrastructure as code such as Terraform or CloudFormation, and CI/CD pipelines such as GitHub Actions
• Experience with orchestration tools such as Flyte, Temporal, Airflow, Prefect, or similar systems
• Experience building laboratory, scientific workflow, LIMS, ELN, data platform, or ML platform products
• Experience designing systems that support auditability, traceability, reproducibility, data provenance, or regulated workflows