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 following clean code principles and engineering best practices
• 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
• Collaborate with multidisciplinary researchers and engineers on software development and productization efforts

• 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
• Team-first, independent, curious, detail-oriented, and adaptable mindset
• CV submitted in English
• Successful completion of a reference check is required before an offer

• 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