Lila Sciences is a startup building an AI platform that trains models on scientific literature and integrates laboratory validation to enable autonomous scientific discovery.
<p><strong>Your Impact at LILA</strong></p> <p>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.</p> <p>We're hiring a <strong>Senior Software Engineer II, Enterprise Platform</strong> to own critical systems across two areas: the <strong>enterprise lifecycle</strong> (multi-tenancy, auth, auditability) and the <strong>developer ecosystem</strong> (public APIs, SDKs, MCP so customers and autonomous agents can interact with Lila's platform) that let customers and developers build on Lila. Our internal scientists across both physical and life sciences are first-class customers of this platform, so you'll build for them as directly as for external developers.</p> <p>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.</p> <p><strong>What You'll Be Building</strong></p> <p>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 build the platform primitives that make that possible.</p> <ul> <li><strong>Multi-Tenancy & Authorization.</strong> Build secure tenant isolation, authentication, authorization, and audit across customer organizations. Implement the access boundaries and isolation guarantees that enterprise and regulated (e.g. GxP, FedRAMP) deployments require. Build resilient backend services in Python/FastAPI. Own schema design for multi-tenant data, tenant-aware query patterns, and operational correctness in a regulated environment.</li> <li><strong>Tenant Self-Serve & Lifecycle.</strong> Build the services behind tenant provisioning, self-serve administration, and the customer onboarding lifecycle. Support billing, pricing, and metering surfaces for enterprise customers.</li> <li><strong>Public & Agent-Facing APIs.</strong> Own and evolve Lila's public APIs (REST, streaming, async) designed for both human developers and autonomous agents as first-class consumers. Ship SDKs and define the tool/function interfaces agents call.</li> <li><strong>MCP & Agent Integration.</strong> Build the integration paths that connect MCPs, agents, and data into the platform.</li> </ul> <p><strong>What You'll Need to Succeed</strong></p> <ul> <li>7+ years of backend software engineering, with meaningful experience in APIs, backend services, or platform infrastructure.</li> <li>Strong expertise in one or more of: API design and versioning, multi-tenancy, authentication/authorization, or backend services at scale.</li> <li>Solid in Python (e.g. FastAPI), Kubernetes, AWS, databases.</li> <li>You care about developer experience — you know what makes APIs easy or painful. You write clear errors and think about backward compatibility.</li> <li>Ship working code regularly. Debug production issues. Own systems end-to-end.</li> <li>Work well across teams. You'll have real overlap with infra, data, apps, and science teams. Communicate tradeoffs clearly and make decisions under ambiguity.</li> </ul> <p><strong>Bonus Points For</strong></p> <ul> <li>Built or maintained multi-tenant SaaS platforms with audit, compliance, or isolation requirements (SOC 2, HIPAA, GxP, FedRAMP).</li> <li>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.</li> <li>Shipped public developer platforms, APIs, or SDKs and understand what makes integrations sticky.</li> <li>Familiarity with MCP, OpenAPI, or OIDC/OAuth 2.0.</li> <li>Worked on tenant isolation patterns (row-level security, schema per tenant, search-path isolation).</li> <li>Experience with policy-based authorization (OPA) or externalized authz.</li> </ul> <p> </p><div class="content-pay-transparency"><div class="pay-input"><div class="description"><p><strong>Compensation</strong></p> <p>We offer competitive base compensation with bonus potential and generous early-stage equity. Your final offer will reflect your background, expertise, and expected impact.</p> <p><strong>U.S. Benefits.</strong> 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.</p> <p><strong>International Benefits.</strong> 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.</p></div><div class="title">Expected Base Salary Range</div><div class="pay-range"><span>$180,000</span><span class="divider">—</span><span>$256,000 USD</span></div></div></div><div class="content-conclusion"><p><strong>About LILA</strong></p> <p>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.</p> <p>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 im