Senior Software Engineer, Scientific System of Record

The role

Senior Software Engineers will build the Scientific System of Record to connect scientific intent to physical reality. You will develop lab execution systems, user interfaces, APIs, and data models using cloud and modern DevOps practices.

What you will do

• Build systems that model scientific intent, experiment planning, and protocol execution
• Design and implement UIs and APIs for scientists, automation, and ML workflows
• Build front-end and backend services
• Develop domain models, schemas, and data contracts across various database types
• Diagnose bottlenecks and improve system performance
• Use AWS, Kubernetes, and DevOps practices to deploy production-grade systems
• Partner with scientists, ML researchers, and other cross-functional teams
• Contribute to architecture discussions, code reviews, and testing practices

Required qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field
• 4-6+ years of engineering experience building and deploying large-scale systems in production
• Strong in either front-end or backend
• Strong expertise in front-end engineering, backend engineering, or data modeling and system design
• Strong experience building modern applications with React and TypeScript
• Experience designing, building, and maintaining APIs, services, and application components
• Experience with SQL and at least one of NoSQL, vector databases, search systems, or data lakehouse architectures
• Experience operating production software, including debugging, monitoring, and performance tuning
• Strong communication skills
• Ability to take ownership of ambiguous technical problems
• Hands-on experience using AI coding assistants or AI-augmented engineering workflows

Nice to have

• Python experience
• Hands-on experience with AWS, GCP, or Azure
• Strong understanding of Kubernetes, containerization, infrastructure as code, and CI/CD pipelines
• Experience with orchestration tools such as Flyte, Temporal, Airflow, or Prefect
• 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

Benefits

• Medical, dental, and vision coverage
• Employer-paid life and disability insurance
• Flexible time off with generous company wide holidays
• Paid parental leave
• Educational assistance program
• Commuter benefits, including bike share memberships for office based employees
• Company subsidized lunch program

About the company

Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges. LILA combines advanced AI models with proprietary AI Science Factory™ instruments into an operating system for science.