Senior Software Engineer, Full Stack

Responsibilities

• Develop high-performance full-stack applications that translate complex biological data and operational needs into intuitive software using Python and modern JavaScript frameworks
• Champion an AI-first mindset, leveraging generative AI tools and LLM-based assistants to accelerate feature development, optimize code quality, and automate routine engineering tasks
• Collaborate with cross-functional domain experts to architect and operate on biological datasets (genomic, diagnostic, or epidemiological), ensuring that surveillance workflows maintain high standards for data integrity, provenance, and security.
• Influence the technical roadmap and long-term evolution of the Biosecurity platform, identifying and mitigating technical debt and architectural bottlenecks before they impact delivery.
• Design and implement robust CI/CD pipelines where automated unit, integration, and security testing are treated as mandatory gates for every code deployment.
• Drive engineering excellence by leading technical design reviews and providing critical feedback on software modularity, while upholding rigorous standards for documentation, observability, and long-term maintainability
• Support production systems by monitoring performance, troubleshooting issues, and continuously improving reliability, including on-call support and triage in off hours

Requirements

• 6-8+ years of professional software engineering experience, with significant full-stack development work, including ownership of complex systems and cross-team technical initiatives.
• Strong proficiency in Python for backend development (our primary programming language).
• Experience building and consuming APIs (REST and/or GraphQL).
• Experience developing modern web frontends using JavaScript/TypeScript and frameworks such as React.
• Demonstrated ability to integrate AI-assisted development tools (e.g., GitHub Copilot, Cursor, or similar) into daily workflows to increase productivity and code reliability
• Proven experience collaborating domain experts (scientific, operations, product, etc) to translate complex biological data (genomic, diagnostic, or epidemiological) into robust software solutions and actionable insights
• Solid grounding in software engineering fundamentals: data structures, system design, version control, and modern CI/CD patterns for automated testing and deployment

Preferred Capabilities and Experience

• Prior experience in bioinformatics, computational biology, public health, or a related domain.
• Familiarity with cloud infrastructure (e.g., AWS) and containerized environments (Docker, Kubernetes).
• Experience with data pipelines, workflow orchestration, or analytics platforms.
• Exposure to regulated or sensitive-data environments (e.g., HIPAA, public health data).
• Demonstrate high levels of ownership and independent execution
• Comfort working in fast-moving, ambiguous problem spaces where requirements evolve
• Flexibility and willingness to work on the highest priority needs of the business