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Salary: USD 192,000 - 272,000 / annual
Lila Sciences is building autonomous science infrastructure—AI systems that design experiments, run them in physical labs, and close the loop across life sciences, chemistry, and materials science. The company is hiring a Staff Engineer, Enterprise Platform to build foundational systems enabling Lila's platform to operate reliably at scale for external customers requiring security, auditability, and operational rigor.
You will drive core enterprise capabilities to production, including multi-tenancy and tenant isolation, enterprise identity and permissions across the full platform lifecycle, metering and billing infrastructure, and audit logging. You will push the frontier by 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 enable customers and third-party agents to 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. It is a high-autonomy, high-impact position. The team moves fast, ships weekly, and expects engineers who thrive in ambiguity and own outcomes.
Key responsibilities include:
- Design and evolve 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. Define how tenant isolation, policy evaluation, and access governance work across the platform.
- Design tenant-aware schemas, metadata systems, and platform primitives supporting 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.
Requirements:
- 8+ 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 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 related field
Bonus:
- Practical experience with agentic systems and workflow automation where models take actions with real operational consequences in regulated environments
- Experience with platforms serving scientific or laboratory data (LIMS, ELN, bioinformatics, or related systems); understanding of provenance and traceability requirements for scientific workflows
- Built self-service enterprise tooling for non-technical administrators with thoughtful UX and API design
- Experience with compliance frameworks: SOC 2, HIPAA, GxP, FedRAMP, or ALCOA+
- Operated multi-tenant SaaS systems at significant scale with strict isolation, reliability, and compliance requirements
