Senior Software Engineer, Data Platform

Profluent is the frontier AI lab for biology. Profluent builds powerful foundation models for all of life's molecules, unlocking solutions that transform medicine, agriculture, and beyond. Founded in 2022 and headquartered in Emeryville, CA, Profluent is backed by leading investors including Altimeter Capital, Bezos Expeditions, Spark Capital, Insight Partners, Air Street Capital, AIX Ventures, and Convergent Ventures and has raised over $150M to date. We’re looking for a Senior Software Engineer to help design, build, and scale Profluent’s data platform. This platform houses data from protein engineering campaigns, including protein designs, experimental results, partner datasets, analytical outputs, and model-ready training data. It enables rapid machine learning, biological discovery, and secure collaboration across internal and external programs. This role is ideal for an engineer who enjoys building robust data systems: secure ingestion pipelines, well-structured warehouses, reliable data models, access controls, auditability, and infrastructure that makes complex scientific data usable at scale. You will work closely with ML, bioinformatics, and program teams to ensure Profluent’s data is organized, governed, accessible, and protected. Responsibilities Design, build, and maintain scalable data infrastructure for protein engineering campaigns, including ingestion, tran [... source excerpt omitted ...] lity checks, schema evolution, versioning, and documentation Collaborate with ML engineers, computational biologists, data scientists, and program stakeholders to understand data requirements and translate them into scalable technical systems Improve engineering quality through thoughtful system design, code review, testing, CI/CD, observability, and maintainable development workflows Contribute to architectural decisions for how Profluent stores, secures, organizes, and uses data across programs and partnerships Qualifications 5+ years of software engineering, data engineering, or data platform experience Strong proficiency in Python and modern software development practices, [... source excerpt omitted ...] s datasets and building systems that make them reliable, discoverable, and usable Ability to work independently, make sound technical decisions, and drive projects from ambiguous requirements to production systems BS, MS, or PhD in Computer Science, Engineering, Data Science, Bioinformatics, or a related technical field, or equivalent practical experience Preferences Experience with scientific, biological, clinical, genomic, laboratory, or high-throughput experimental data Experience managing external partner, customer, or restricted-access datasets Familiarity with data governance, lineage, metadata systems, schema registries, or data catalogs Experience with research data sy