Senior Software Engineer, Scientific System of Record

Your Impact at LILA

Join us in shaping the future of science! We are seeking Senior Software Engineers with full stack experience to join our Scientific System of Record Team (SSR), where you’ll collaborate with software engineers, lab scientists, and machine learning engineers to build cutting-edge tools for automated scientific analysis and more. If you thrive in a collaborative, fast-paced environment and bring best practices in git, development workflows, and user-centered design, we want to hear from you!

About The Team

The Scientific System of Record Team (SSR) builds the memory layer for Lila's operations. It answers two questions:what did we plan to build? and what actually happened? These systems connect scientific intent to physical reality. Together with the data and automation teams, their systems ensure reproducibility and close the Design-Build-Test-Learn (DBTL) loop.

What You'll Be Building

• Lab Execution and Scientific Workflows: Build systems that model scientific intent, experiment planning, protocol execution, sample and asset state, operational events, and results capture across complex lab workflows.
• User Interfaces and APIs: Design and implement high-quality, secure, and well-documented UIs and APIs that support scientists, automation systems, ML workflows, and AI-driven applications.
• Application Development: Build front-end and backend services with a focus on performance, maintainability, and reliability.
• Data and System Modeling: Develop domain models, schemas, indexes, and data contracts across SQL, NoSQL, vector databases, data lakehouses, and other scientific data systems.
• Reliability, Performance, and Scale: Diagnose bottlenecks, improve system performance, and contribute to observability, reliability, and operational excellence for production systems.
• Cloud and Infrastructure: Use AWS services, Kubernetes, and modern DevOps practices to build and deploy production-grade systems.
• Cross-Functional Collaboration: Partner with scientists, ML researchers, platform engineers, data engineers, automation teams, and product managers to translate scientific and operational needs into software.
• Engineering Quality: Contribute to architecture discussions, code reviews, testing practices, documentation, and shared engineering standards.

What You'll Need To Succeed

• 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. You must be strong in either front-end or backend.
• 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 building modern applications with React and TypeScript; Python experience is strongly preferred.
• Application and API Development: Experience designing, building, and maintaining APIs, services, and application components with a focus on reliability, performance, and maintainability.
• Databases and Data Modeling: Experience with SQL and at least one of NoSQL, vector databases, search systems, or data lakehouse architectures; familiarity with schema design, indexing, and query optimization.
• Production Systems: Experience operating production software, including debugging, monitoring, performance tuning, and improving reliability over time.
• Collaboration: Strong communication skills and a track record of working cross-functionally with engineers, product teams, scientists, or other domain experts.
• Problem Solving: Ability to take ownership of ambiguous technical problems, make practical trade-offs, and deliver maintainable solutions.
• Hands-on experience using AI coding assistants or AI-augmented engineering workflows to improve productivity.

Bonus Points For

• Cloud and DevOps: 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.
• Orchestration Systems: 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.

About LILA

Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges. We believe science is the most inspiring frontier for AI. Rather than hard-coding expert knowledge into tools, LILA builds systems that can learn for themselves.

LILA combines advanced AI models with proprietary AI Science Factory™ instruments into an operating system for science that executes the entire scientific method autonomously, accelerating discovery at unprecedented speed, scale, and impact across medicine, materials, and energy. Learn more at www.lila.ai.

Guided by our core values of truth, trust, curiosity, grit, and velocity, we move with startup speed while tackling problems of historic importance. If this sounds like an environment you'd love to work in, even if you don't meet every qualification listed above, we encourage you to apply.

We’re All In

Lila Sciences is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.

Information you provide during your application process will be handled in accordance with our Candidate Privacy Policy.

A Note to Agencies

Lila Sciences does not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to Lila Sciences or its employees is strictly prohibited unless contacted directly by Lila Science’s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of Lila Sciences, and Lila Sciences will not owe any referral or other fees with respect thereto.