Lead, mentor, and grow a team of software engineers across multiple levels (staff, senior, mid-level, and junior), fostering a culture of technical excellence, collaboration, and continuous improvement
Own the technical roadmap for variant classification systems, aligning engineering priorities with business objectives and scientific needs
Partner with product management, data science, variant science, and bioinformatics stakeholders to define requirements, set priorities, and deliver impactful solutions
Drive the design and delivery of tools that define, store, and provide meaningful variant, sample, and test-level information to support accurate variant interpretation and report generation
Oversee development and maintenance of systems that translate raw bioinformatic data into variant and sample-level information, including registration, normalization, observation groups, and quality metrics
Establish and maintain engineering standards, processes, and best practices across the team, including code review, testing, CI/CD, and incident response
Manage team capacity, hiring, performance reviews, career development, and succession planning
Drive architectural decisions that scale storage and processing of sample-level information to support growing data needs
Champion automation of evidence placement and classification for variant interpretation
Support test content and assay development initiatives through effective resource allocation and technical guidance
Communicate technical strategy, progress, and risks to senior leadership and cross-functional partners
Define and evolve the team's processes and governance for applying AI and LLM tools to variant classification workflows, ensuring responsible use aligned with scientific rigor and regulatory requirements
Remove blockers, manage dependencies across teams, and ensure timely delivery of commitments
Requirements
Bachelor's degree
6 or more years of related professional software engineering experience
3 or more years in IT leadership roles
3 or more years' experience managing software engineering teams, including hiring, performance management, and career development
6 or more years' experience and technical foundation in Python, relational databases, cloud platforms (AWS, Azure, or GCP), and modern web development frameworks
6 or more years' demonstrated experience delivering complex software systems using RESTful APIs, microservices architecture, and CI/CD pipelines
3 or more years' experience managing teams working with front-end technologies (e.g., React, Angular, Vue.js, JavaScript/TypeScript)
6 or more years' experience and proven ability to define technical vision, set priorities, and drive execution across multiple concurrent workstreams
3 or more years' experience and track record of building and developing high-performing engineering teams across multiple experience levels