Profluent
Software Engineering Manager, Lab Informatics Platform
Emeryville, California, United States; Hybrid (2-3 days on-site)
Work authorization required$180k-$250kDetected 30 days ago
PythonBackend DevelopmentCode ReviewCI/CDMachine LearningSparkAgileStakeholder ManagementBioinformaticsCRISPRResearchLeadershipCommunication
About the role
- The ideal candidate is an experienced people manager with a strong technical foundation and sound product judgment.
- Sponsorship will not be provided now or at any time in the future for this position.
- Hiring Salary Range $180,000 - $250,000 USD
Responsibilities
- Lead, mentor, and grow a software engineering team focused on lab informatics, scientific data infrastructure, and scientist-facing applications
- Own and communicate the roadmap for Profluent's lab informatics platform, balancing scientific impact, user needs, engineering effort, usability, scalability, and long-term data strategy
- Architect and guide delivery of systems that support sample tracking, assay data capture, Benchling integration, lab automation, experimental metadata, and analysis workflows
- Design robust data models for protein engineering and gene editing experiments, including constructs, samples, reagents, cell systems, assay results, metadata, and experimental lineage across mammalian and bacterial workflows
- Partner closely with scientists, automation engineers, data scientists, and ML researchers to understand workflows, identify pain points, define requirements, prioritize tradeoffs, and translate complex laboratory needs into scalable software solutions that accelerate Profluent's design-build-test-learn cycle
- Establish strong engineering and product practices across architecture, technical design, code review, testing, CI/CD, documentation, stakeholder communication, feedback loops, success metrics, adoption, and agile delivery
Requirements
- 7+ years of software engineering experience, including at least 2 years managing or leading engineers
- Strong technical leadership skills, with a track record of architecting and delivering production-quality software systems through teams
- Proficiency with Python, backend development, databases, APIs, and modern software engineering workflows, with the ability to guide technical design and implementation
- Experience with Benchling, lab automation, instrument data ingestion, sample tracking, or high-throughput experimental data
- Experience with data generated from mammalian or bacterial cell systems, gene editing, protein engineering, or related biological workflows
- BS, MS, or PhD in Computer Science, Bioengineering, Computational Biology, or a related field
- Experience building or leading teams that build scientific data platforms, LIMS integrations, research software, or scientist-facing applications, including data modeling and database design for complex scientific or experimental workflows
- Demonstrated ability to work closely with scientists and technical stakeholders to translate ambiguous laboratory workflows into reliable software systems, define requirements, prioritize tradeoffs, and drive adoption of internal tools
- Frontend web development experience and interest in building intuitive scientist-facing user interfaces
- High-growth opportunity with meaningful impact on the future of protein design
- Competitive compensation package with equity participation
- 401(k) with a strong employer match
- Comprehensive benefits including health/dental/vision insurance
- Generous PTO policy and commitment to work-life balance
Skills
- Profluent is an AI-first protein design company.
Compensation
- Hiring Salary Range $180,000 - $250,000 USD
Equal opportunity
- equal opportunity employer promoting diversity and inclusion in the workspace.
Visa & Work Authorization
- Applicants must have ongoing work authorization in the United States that does not require employer sponsorship.
- Sponsorship will not be provided now or at any time in the future for this position.
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This listing is sourced directly from Profluent's careers page and normalized into a canonical job model.