Top Biotech Software Engineer Jobs

Lead the design and development of scalable full-stack systems for Genomics AI initiatives. Architect distributed microservices, build React and Node.js applications, optimize PostgreSQL and Redis systems, integrate generative AI and agentic workflows, and manage GCP infrastructure and CI/CD. Mentor engineers, guide architectural decisions, drive cross-team technical initiatives, and deliver high-quality software for precision medicine and clinical care applications.

Lead the technical design and delivery of electronic prescribing modernization for OncoEMR. Build and review full-stack software using C#, VB.NET, React, and .NET services; modernize legacy WebForms workflows; develop safety-critical prescribing features; partner with product, QA, design, clinical, and vendor teams; manage complex projects from planning through rollout; and mentor engineers through code reviews, pairing, and design guidance.

Leads enterprise application projects and serves as the technical authority for NetSuite and related business systems. Responsibilities include configuration, customization, integrations, workflow improvements, troubleshooting production issues, data-quality initiatives, technical standards, deployments, documentation, user training, and mentoring. Partners with technical and business teams to deliver scalable solutions across a polyglot cloud environment.

Lead a full‑stack engineering team to build scalable frontend and backend systems, make architectural decisions, prioritize the product roadmap with stakeholders, build data pipelines for ML, support deployments and DevOps, and manage external engineers to deliver product objectives.

Develop software for clinical brain-computer interface applications, including BCI data curation, neural decoding algorithms, simulated and real-data evaluation, hardware-in-the-loop testing, code reviews, and feature development. Collaborate with engineering, neuroscience, machine learning, and quality teams to define requirements and support clinical studies. Regular travel between Austin and Oakland offices is required.

Build internal software products, automations, workflows, and data-flow improvements that enhance business operations. Translate organizational needs into working tools, drive adoption, advise leadership on engineering practices, and support cross-functional change. Approximately 80% of the role involves hands-on software development, with the remainder focused on internal consulting and strategic guidance.

Build and maintain full-stack features for Benchling’s workflow engine, recipes, assays, and related life sciences products. Develop backend services, frontend interfaces, workflow data models, and AI-enabled functionality. Collaborate with engineering, product, design, and AI teams; write tested and documented code; participate in code reviews and on-call support; and work onsite in San Francisco three days per week.

Build and operate backend-focused production software, APIs, integrations, databases, distributed systems, and asynchronous workflows. Develop AI-enabled and agentic systems with retrieval, tool use, evaluation, permissions, observability, and reliability controls. Own products from definition through iteration, collaborate with data engineering, data science, and SRE, make pragmatic technical tradeoffs, and mentor engineers.

Lead full‑stack development of React Native mobile apps and Node.js backends for digital therapeutics. Own architecture, build CI/CD and AWS infrastructure, design multi‑agent AI workflows, mentor engineers, and resolve cross‑cutting production issues.

Lead the development, deployment, administration, and sustainment of enterprise engineering applications, including PLM, CAD/PDM, MBSE, and change-management platforms. Build dashboards, integrations, ETL pipelines, workflow automations, and AI-enabled tools using technologies such as SQL, Python, and Power BI. Manage data governance, compliance documentation, system releases, vendor escalations, user training, platform evaluations, and engineering application adoption across hardware and software development teams.