The next frontier is authoring new biology, and with AI, we have the power to write the future—creating solutions that transform medicine, agriculture, and beyond. Backed by Insight and Air Street.
About the role
We’re looking for a Director of Software and Data Engineering to lead Profluent’s software engineering function and build the platform connecting AI-driven protein design, high-throughput experimental screening, and quantitative data analysis.
What they're looking for
- 8+ years of software engineering experience, including 3+ years managing or leading engineers
- BS, MS, or PhD in Computer Science, Bioengineering, Computational Biology, or a related field, or equivalent practical experience
- Track record of leading teams that architect and deliver production-quality, data-intensive software platforms
- Strong technical foundation in Python, backend systems, databases, APIs, cloud infrastructure, and modern software development practices
- Experience designing data architectures, schemas, and domain models for complex scientific, experimental, or similarly interconnected workflows
- Demonstrated ability to translate ambiguous user and scientific needs into reliable systems, make sound technical and product tradeoffs, and drive adoption
More about this role
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 Director of Software and Data Engineering to lead Profluent’s software engineering function and build the platform connecting AI-driven protein design, high-throughput experimental screening, and quantitative data analysis.
You’ll own the software and data architecture connecting computational designs to the constructs, samples, assays, and measurements generated through automated laboratory workflows. Your team will build the scientist-facing tools, integrations, and data systems needed to manage experimental data at scale, preserve lineage and context, and turn results into reliable inputs for analysis, machine learning, and the next round of design.
The ideal candidate is an experienced engineering leader with...
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