Staff/ Principal Software Engineer, Scientific System of Record

The role

You will define and build an AI-driven scientific platform. You will serve as a technical leader for systems connecting scientific intent, laboratory execution, data capture, and AI-driven analysis.

What you will do

• Define architectural direction for the AI Lab Execution System and related Scientific System of Record capabilities.
• Design systems that model scientific intent, experiment planning, protocol execution, sample and asset state, operational events, and results capture.
• Lead the design of high-performance, secure, and well-documented UIs and APIs.
• Establish durable domain models, schemas, and data contracts across various database types.
• Set technical standards for high availability, low latency, observability, fault tolerance, and operational excellence.
• Guide the use of AWS services, Kubernetes, and modern DevOps practices.
• Partner with scientists, ML researchers, platform engineers, data engineers, automation teams, and product leaders.
• Mentor engineers, drive architecture reviews, and establish patterns, tools, and practices.

Required qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
• 8-15 years of engineering experience building and deploying large-scale systems in production.
• Strong in either front-end or backend.
• Strong expertise in at least one of the following areas: front-end engineering, backend engineering, or data modeling and system design.
• Strong experience building modern applications with React and TypeScript.
• Deep experience designing scalable application architectures, APIs, domain models, schemas, indexes, data contracts, and distributed data systems.
• Strong experience with SQL and at least one of NoSQL, vector databases, graph databases, search systems, or data lakehouse architectures.
• Proven ability to design APIs, platform abstractions, and integration patterns.
• Experience working in life sciences, materials science, ML platforms, laboratory systems, automation platforms, or other research-heavy and data-intensive environments.
• Experience designing production systems with strong observability, reliability, incident response, performance tuning, and long-term maintainability.
• Ability to mentor senior engineers, align stakeholders, make clear technical trade-offs, and drive complex initiatives.
• Strong listening skills and the ability to explain complex technical ideas.

Nice to have

• Python experience is strongly preferred.
• Experience with orchestrators tools (Airflow, Prefect, Temporal, Dagster).
• Familiarity with data science and ML libraries (pandas, numpy, scipy, jax, pytorch).
• 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. The company combines advanced AI models with proprietary AI Science Factory™ instruments into an operating system for science.