Principal Software Engineer - Variant Knowledge Platform

Labcorp•Durham, NC

9d•$180,000 - $205,000•Remote

About The Position

Labcorp Genetics is seeking a Principal Software Engineer to help shape and build the Variant Knowledge Platform, the team and systems responsible for variant identity, classification, and annotation. The platform provides the authoritative source of variant truth that powers clinical interpretation, curation, and analytics across the organization. In this role you will own ambiguous, org-spanning technical problems end to end, define the architectures and API contracts that platform consumers build on, drive cross-team initiatives, and raise the engineering bar for teams well beyond your own. Because variant identity and classification data flow directly into clinical reports and downstream analytics, the systems you design must be correct, versioned, and durable.

Requirements

Bachelor's Degree.
Five or more years of experience in REST API and contract design, including versioning and depreciation strategy and secure service-to-service authentication (e.g., Okta-based identity).
Two or more years of experience designing and operating cloud-based services on AWS.
Five or more years of experience in a primary backend programming language used for data-intensive services (e.g., Python).

Nice To Haves

One or more years of experience in genomics or bioinformatics, such as variant interpretation, clinical genetics, HGVS/variant nomenclature, gene/transcript annotation, or evidence-based classification.
Two or more years of experience with event-driven and asynchronous messaging architectures (e.g., AWS SQS) and building clean REST gateways in front of them.
One or more years of experience working in a regulated or clinical environment, including version pinning and validation needs driven by regulatory requirements.
Experience building multi-tenant, platform-as-a-product systems serving multiple internal and external consumers.
Experience delivering multi-tenant observability and cross-cutting reliability for shared platform services.
Experience executing large one-time data migrations and backfills with provenance and validation guarantees.
Experience designing, building, and operating large-scale, distributed backend systems and data platforms in production.
Experience defining and driving operational excellence across testing strategy, observability, health monitoring, and production reliability.
Strong data modeling skills for systems where data consistency and correctness are critical, including schema evolution and migration at scale.
Experience of org-wide technical leadership: setting architecture across teams, authoring ADRs or equivalent design records, and building alignment across engineering and cross-functional partners on ambiguous, high-impact initiatives.
Excellent written and verbal communication, including the ability to tailor technical messaging from engineers to executive audiences.
Familiarity with analytics data ecosystems (e.g., Snowflake) and the trade-offs between batch or lagged and real-time data paths.

Responsibilities

Own the technical design for large, ambiguous, open-ended problems that span the Variant Knowledge Platform and the broader interpretation stack, where there is no clear off-the-shelf solution.
Define and evolve the data models for variant identity, classification, and annotation, holding a high bar for correctness and consistency.
Design production-grade, versioned REST API contracts, secured via the platform's identity provider (Okta), that internal consumers and enterprise clients integrate against, including versioning, deprecation, and governance strategies.
Lead the evolution of the systems that turn raw bioinformatic data into trustworthy variant- and sample-level information, and the pipelines that source, maintain, and serve variant annotations, toward real-time, multi-tenant operation.
Drive the architecture for automating evidence placement and classification, and for scaling the storage and retrieval of sample- and variant-level data as volume and client count grow.
Define org-wide system architectures and rally engineers and stakeholders around them through clear rational, written design documents, and Architecture Decision Records (ADRs).
Lead cross-team technical programs as a named principal-level lead, coordinating design, sequencing, and delivery across platform, boundary/tenancy, and curation teams, and represent the platform in the Architecture Review Forum.
Set the strategy for system operability: testing, observability (including multi-tenant observability), health monitoring, reliability, and on-call practices under a “you build it, you run it” model.
Lead large-scale data migration and backfill efforts, such as consolidating legacy interpretation data into VKB, with the rigor, staging, and validation gates such work demands.
Shape the platform's role in enabling future test content and assay development through its data and services.
Mentor and level up engineers across multiple teams through technical guidance, design review, and role-modeling, multiplying the org's overall engineering capability.
Partner with cross-functional stakeholders across product, curation science, and clinical to identify business opportunities enabled by the platform and align technical strategy to them.
Communicate technical vision and trade-offs clearly to audiences ranging from individual engineers to executives, securing buy-in for direction-setting decisions.