Sr Principal/ Principal Software Engineer, Scientific System of Record

• 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. You must be strong in either front-end or backend.
• Strong expertise in at least one of the following areas, with the ability to reason across all three: 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.
• Systems and Data Architecture: Deep experience designing scalable application architectures, APIs, domain models, schemas, indexes, data contracts, and distributed data systems.
• Databases: Strong experience with SQL and at least one of NoSQL, vector databases, graph databases, search systems, or data lakehouse architectures.
• API and Platform Design: Proven ability to design APIs, platform abstractions, and integration patterns that are reliable, maintainable, and easy for other teams to build on.
• Scientific or Data-Intensive Domains: Experience working in life sciences, materials science, ML platforms, laboratory systems, automation platforms, or other research-heavy and data-intensive environments.
• Operational Excellence: Experience designing production systems with strong observability, reliability, incident response, performance tuning, and long-term maintainability.
• Technical Leadership: Ability to mentor senior engineers, align stakeholders, make clear technical trade-offs, and drive complex initiatives from ambiguity to production.
• Communication and Collaboration: Strong listening skills and the ability to explain complex technical ideas to scientists, engineers, product leaders, and executives.
• Hands-on experience using AI coding assistants or AI-augmented engineering workflows to improve productivity.

• Orchestration Systems: Experience with orchestrators tools (Airflow, Prefect, Temporal, Dagster).
• Familiarity with Python for Science: 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.

We offer competitive base compensation with bonus potential and generous early-stage equity.

Your final offer will reflect your background, expertise, and expected impact.

U.S. Benefits. Full-time U.S. employees receive a comprehensive benefits program including medical, dental, and vision coverage; employer-paid life and disability insurance; flexible time off with generous company wide holidays; paid parental leave; an educational assistance program; commuter benefits, including bike share memberships for office based employees; and a company subsidized lunch program.

International Benefits.

Full-time employees outside the U.S. receive a comprehensive benefits program tailored to their region.

USD salary ranges apply only to U.S.-based positions; international salaries are set to local market.

Lila Sciences is building Scientific SuperintelligenceTM 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 FactoryTM 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.

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.

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