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Design and build integrations for AI-driven applications, develop databases, optimize performance, collaborate with scientists, and drive large-scale systems deployment.

As a Staff Software Engineer, you will develop UIs, APIs, and databases for an AI-driven scientific platform, ensuring performance and integration with various systems. Collaborate with researchers and engineers to enhance scientific workflows and scale large systems.

Lead and build a test automation platform and quality engineering practice for AI-driven scientific and lab automation products. Architect CI/CD test execution, AI-driven test tooling, eval pipelines, and lab QC frameworks (ALCOA+). Hire and lead a small platform team, set standards and metrics, drive platform adoption, and deliver measurable improvements in signal, flake rate, and time-to-production.

Build and operate enterprise developer platform features: multi-tenancy, authz/audit, tenant lifecycle and provisioning, public/streaming APIs and SDKs, and integrations for MCPs/agents. Ship backend services in Python/FastAPI, design tenant-aware schemas and isolation, support billing/metering, debug production issues, and collaborate across infra, data, apps, and science teams to meet regulated deployment requirements.

The role involves researching and developing training strategies for large language models, focusing on their applications in scientific reasoning and performance evaluation.

Design and maintain large-scale distributed training systems, optimize performance for ML models, and improve training efficiency.

As a Senior Software Engineer, focus on backend development and AI integration for scientific applications, building systems that leverage advanced AI techniques.