Staff Engineer, Enterprise Externalization
Lila Sciences · San Francisco, CA USA · San Francisco, CA
CHECKED 14H AGO
Bio & Science AIonsitestaff$192k–$272k
At a glance
Highlights
- Build enterprise platform enabling autonomous science at scale for pharma customers.
- Drive multi-tenancy, audit logging and billing infrastructure to production.
- Build AI-native external APIs and agentic self-service tenant management.
What they offer
- Competitive base compensation with bonus potential
- Generous early-stage equity
- Medical, dental and vision coverage
- Employer-paid life and disability insurance
- Flexible time off with company holidays
- Paid parental leave
- Educational assistance program
- Commuter benefits
- Company subsidized lunch program
Ideal candidate
High-autonomy builder who thrives in ambiguity and owns outcomes end-to-end. You care about secure, scalable enterprise platforms that let large scientific organizations adopt AI-driven discovery.
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 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
Lab profile
About Lila Sciences
Building an autonomous science platform where AI, automation, and biology co-evolve for medicine and materials.
What they build
- Autonomous Science Platform
- AI-designed biologics validated in wet-lab
- Electro-optic materials and photonic devices
Known for
- Large-scale automated data generation
- High-throughput protein purification and analytics
- Protein design and BioML modeling
- Robotic orchestration and lab simulation