Software Engineer – Research Data Platform

• Design, implement, and maintain robust, scalable data schemas and storage solutions optimized for high-performance AI workloads
• Benchmark, profile, improve, and extend distributed storage using chunking, compression, parallelization, and custom solutions
• Develop and maintain high-quality, production-ready data systems
• Build clean, typed, well-documented APIs for researchers, engineers, and AI agents
• Work with researchers and product engineers to scope needs, align priorities, and own projects end-to-end
• Monitor, profile, and optimize database queries, storage read/write paths, pipeline bottlenecks, and cloud infrastructure costs
• Implement data validation, testing, versioning, and access control with platform engineers
• Participate in system-design, take-home, presentation, technical Q&A, and executive interview stages

• Deep, production-level knowledge of Python
• Strong hands-on experience with modern Python data tools and frameworks, including Pydantic, SQLAlchemy, Alembic, object storage abstractions, and FastAPI or similar frameworks
• Expertise in relational database management systems such as PostgreSQL, including schema design, indexing strategies, and query optimization
• Experience designing API surfaces
• Exposure to protocols for programmatic and agent access such as the Model Context Protocol (MCP)
• Strong belief that data infrastructure is a product and commitment to usability for non-technical stakeholders
• Submit CV in English
• Successful completion of a reference check is required for an offer
• Biotech/life sciences experience, startup experience, distributed array storage, workflow orchestration, frontend/visualization, and proactive communication are bonuses, not requirements

• Competitive salary and equity package
• Flexible work arrangements, including remote options
• Collaborative and mission-driven work environment
• Opportunity to help grow the data platform and accelerate discovery in cancer biology