Senior Manager, Software Development Engineering

Labcorp•San Francisco, CA

13h•$140,000 - $198,000•Hybrid

About The Position

Labcorp is seeking a Senior Manager, Software Engineering - Variant Classification to join our Labcorp Genetics team. This leader will build, develop, and manage a high-performing engineering team responsible for the systems and tools that power variant interpretation, classification, and report generation. This is a full-time, exempt (salaried) position assigned to a First Shift schedule, with standard business hours of Monday through Friday, 8:00 a.m. to 5:00 p.m. in your local time zone. Business needs may occasionally require flexibility in work hours, including earlier, later, or additional hours, with reasonable notice provided when possible. Applicants who live within 35 miles of either the Burlington, NC or Durham, NC location will follow a hybrid schedule. This schedule includes a minimum of three in-office days per week at an assigned location, either Burlington or Durham, supporting both collaboration and flexibility.

Requirements

Bachelor's degree
6 or more years' 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

Nice To Haves

Master's Degree or Ph.D. in Bioinformatics/Computational Biology, Computer Science, or life sciences with 4 or more years' related professional software engineering experience
5 or more years of engineering management experience, including managing senior and staff-level engineers
5 or more years' experience with bioinformatic tools, annotation pipelines, and genomic data resources (e.g., ClinVar, gnomAD, HGMD)
5 or more years' experience with Spark, text mining, natural language processing, semantic enrichment, ontologies, data mining, or machine learning/AI
5 or more years' experience with public-domain biomedical terminologies (e.g., MeSH, NCIt, HGNC)

Responsibilities

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
Proven ability to define technical vision, set priorities, and drive execution across multiple concurrent workstreams
Track record of building and developing high-performing engineering teams across multiple experience levels
Familiarity with variant databases and the clinical variant interpretation landscape
Experience translating complex scientific questions into information solutions and engineering roadmaps
Experience managing teams in regulated or clinical environments
Owns and delivers product or platform goals across multiple years and teams, setting a high standard for technical outcomes, team health, and delivery
Defines the vision, scope, and technical approach for large, business-impacting projects with organization-wide implications
Identifies, prioritizes, and drives solutions to ambiguous, open-ended problems, empowering the team to deliver with autonomy
Influences the roadmaps of partner teams to align with and achieve broader business goals
Serves as a role model for engineering leadership, balancing technical depth with people management
Effective verbal and written communicator with both scientific and non-scientific audiences, including senior leadership
Cultivates a team culture that leverages modern tools such as GitHub Copilot, Claude Code, or similar LLM tools to accelerate development, testing, and documentation
Builds an inclusive, psychologically safe team environment that attracts and retains top engineering talent