Top Biotech Software Engineer Jobs

Leads architecture, roadmap, execution, and team development for high-performance BCI software spanning embedded, edge, and distributed systems. Establishes engineering practices, testing, infrastructure, and documentation for regulated medical devices; coordinates hardware, clinical, AI, cybersecurity, and regulatory dependencies; manages hiring, resources, budgets, and technical delivery while remaining engaged in architecture and critical problem-solving.

Leads a four-person software and data team delivering business reporting, analytics, data integrations, internal applications, and workflow automation. Translates Finance and operational requirements into secure, scalable systems while supporting ERP modernization, data governance, application development, deployment, production support, and audit-ready controls. Partners with executives, functional leaders, enterprise IT, and implementation vendors to prioritize initiatives and improve business processes.

Build and lead imaging software infrastructure spanning microscope acquisition, image processing, high-throughput ML pipelines, data visualization, quality control, and laboratory automation. Scale research prototypes into reliable systems processing millions of images daily while ensuring data integrity, lineage, reproducibility, and observability. Partner with laboratory, ML, and microscopy scientists to translate research needs into production software, own architectural decisions, document systems, and mentor engineers.

Lead the architecture, development, and scaling of backend services, APIs, distributed systems, data pipelines, agent clouds, and platform infrastructure. Build reliable third-party integrations, improve observability and security, shape engineering standards and CI/CD practices, and support DevOps and troubleshooting. Contribute to AI agent harness selection, prompt optimization, and evaluation systems while making architecture and operational decisions in a fast-paced startup environment.

Build and deploy production AI-powered systems for biopharma customers, translating ambiguous clinical and financial workflows into core platform capabilities. Develop Django services and APIs, AWS Bedrock agent workflows, data integrations, monitoring, feedback loops, and customer-facing interfaces. Own deployments end to end, contribute production code through the core codebase, identify reusable patterns, and influence product architecture and roadmap. Occasional travel to customer locations is required.

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

Designs, builds, tests, and maintains full-stack features across Angular, Java, and Spring applications. Owns work from technical design through production deployment, contributes to system design, CI/CD, observability, testing, and operational resilience, and collaborates with Product, DevOps, and QA. Uses agentic coding tools such as Claude Code and Cursor under team guardrails. Participates in code reviews, audits, documentation, debugging, and continuous engineering improvements.

Lead development and commercialization of intradermal biosensor software, authoring tested mobile/server/GUI code and SDKs, ensuring regulatory quality-system compliance, mentoring engineers, estimating capacity, and maintaining production services.

Lead technical design and delivery of software projects across the SDLC. Mentor developers, collaborate with product and IT leadership, integrate AI tools, drive DevOps and process improvements, ensure PHI/security compliance, and present performance findings to senior leadership while participating in agile ceremonies.

Design, develop, and maintain scalable data platforms and batch/streaming pipelines. Implement data scientist algorithms, drive engineering best practices, mentor junior engineers, improve processes and infrastructure, and contribute to distributed system software and CI/CD in an Agile environment.