Your Impact at LILA
Lila Sciences is building the infrastructure for autonomous science — AI systems that design experiments, run them in physical labs, and close the loop across life sciences, chemistry, and materials science. Our platform enables this to operate reliably at scale for external customers who require security, auditability, and operational rigor.
We’re hiring a Principal Engineer, Enterprise Platform to build the foundational systems that make Lila ready for the world’s largest pharmaceutical and research organizations.
Today we have the beginnings of multi-tenancy, identity and granular permissions and scopes, audit infrastructure, usage and billing. Enterprise customers require significantly more. You will drive core enterprise capabilities to production: multi-tenancy and tenant isolation, enterprise identity and permissions to support the full lifecycle of the Lila Platform, metering and billing infrastructure, audit logging, etc. You will push the frontier — building agentic AI-powered systems for self-service tenant management, intelligent customer observability, automated compliance workflows, Lila SDK, MCP, and AI-native external APIs that let customers and third-party agents interact programmatically with Lila's platform.
This is a deeply technical senior individual contributor role focused on defining and building correct, secure, and scalable platform infrastructure. This is a high-autonomy, high-impact role. We move fast, ship weekly, and expect engineers who thrive in ambiguity not ones who wait for requirements to be handed to them. You will own outcomes.
What You'll Be Building
Enterprise infrastructure is foundational to making autonomous science deployable in the real world. The systems built in this role will determine how large organizations safely adopt, govern, and scale AI-driven scientific workflows across teams, data domains, and regulatory environments.
You’ll help define the platform primitives that make that possible.
- Design and evolve the core identity systems powering Lila’s enterprise platform — organizations, groups, roles, SCIM provisioning, seat lifecycle management, and fine-grained authorization across experiments, datasets, models, and scientific workflows. You’ll define how tenant isolation, policy evaluation, and access governance work across the platform.
- Design tenant-aware schemas, metadata systems, and platform primitives that support highly heterogeneous scientific data across life sciences and materials science workloads. Drive architectural decisions around scalability, reliability, retention, and operational correctness.
- Architect systems for tenant provisioning, usage metering, billing, data migrations, compliance workflows, and operational automation. Push toward self-service and agentic operational workflows that reduce manual intervention while maintaining strong safety guarantees.
- Operate as a senior technical leader across platform engineering, infrastructure, security, AI/ML, and scientific application teams. This is a hands-on Principal Engineer role with broad architectural influence, high autonomy, and direct ownership of critical platform systems.
What You'll Need to Succeed
- 12+ years of software development experience, with a focus on Enterprise SaaS product development
- Deep expertise in enterprise SaaS platform systems: authentication/authorization (OAuth 2.0, OIDC, SAML), multi-tenancy, RBAC, billing/metering, configurations, SDK and APIs
- Experience with modern cloud-native architectures (Kubernetes, Terraform, AWS/GCP) and event-driven systems, familiarity with infrastructure-as-code and containerized deployments
- Track record building enterprise platforms in high-growth environments where speed-to-value mattered as much as long-term architecture
- Strong cross-functional communication skills and the ability to influence architecture across teams.
- Hands-on coding in Python and modern backend frameworks (FastAPI, async Python)
- BS, MS, or Ph.D. in Computer Science or a related field of study
Bonus Points For
- You have practical experience with agentic systems and workflow automation where models take actions with real operational consequences in regulated environments.
- You’ve worked on platforms serving scientific or laboratory data such as LIMS, ELN, bioinformatics, or related systems, and understand the provenance and traceability requirements associated with scientific workflows.
- You’ve built self-service enterprise tooling for non-technical administrators and have thought carefully about the UX and API design required to make those systems usable.
- Experience with compliance frameworks: SOC 2, HIPAA, GxP, FedRAMP, or ALCOA+
- You’ve operated multi-tenant SaaS systems at significant scale with strict isolation, reliability, and compliance requirements.
Compensation
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.
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.
Similar Jobs
What you need to know about the San Francisco Tech Scene
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine
