[Hiring] Lead Software Quality Engineer @UnitedHealth Group

Role Description

The Clinical Decision Support (CDS) Engineering team, a unit within the Optum Insight Technology organization, is responsible for building commercial products helping payers and providers with administrative and clinician focused CDS solutions. We are seeking a Lead Software Quality Engineer to help ensure the reliability, safety, and effectiveness of a mission critical, AI/ML enabled clinical software platform. This role will partner closely with Product Management, Software Engineering, Data Engineering, and ML teams to identify the highest risk areas of the product and guide teams in building robust, scalable, and risk focused test automation.

This role is ideal for a quality leader who blends deep technical testing expertise, systems thinking, and a risk based mindset, and who is excited about applying AI/ML techniques to modernize test automation.

You’ll enjoy the flexibility to work remotely from anywhere within the U.S. as you take on some tough challenges. For all hires in the Minneapolis or Washington, D.C. area, you will be required to work in the office a minimum of four days per week.

Primary Responsibilities

• Partner with Product, Engineering, Data Engineering, and ML teams to identify, quantify, and continuously reassess the highest functional, clinical, data, operational, and security risks across the platform.
• Define and socialize a risk-based quality strategy (test scope, depth, automation targets, environments, and gates) aligned to patient impact and business priorities.
• Provide quality leadership for release readiness by defining meaningful quality signals/metrics, communicating tradeoffs, and influencing go/no-go decisions.
• Own the technical direction for automation frameworks and test infrastructure across layers (data pipelines, APIs/services, AI/ML decision workflows, admin/config portals, and analytics/reporting).
• Establish quality engineering standards (test pyramid strategy, coding patterns, reliability, and maintainability) and drive consistent adoption across teams.
• Enable engineering teams to build, run, and own automated tests in CI/CD through coaching, reusable libraries, and guardrails (not by becoming a bottleneck).
• Advance modern practices such as contract testing, data quality checks, and synthetic test data strategies.
• Partner with ML and data teams to define and automate validation of training/inference data quality, feature/label integrity, and model input/output edge cases.
• Work with architects and AI/ML engineers to define quality approaches for model monitoring (drift, bias/fairness as applicable, performance degradation) and ensure signals are actionable for operations and releases.
• Apply or experiment with AI-assisted testing (e.g., test generation/maintenance, intelligent test selection, anomaly detection) to improve automation effectiveness.
• Ensure quality practices support required traceability, auditability, and explainability for clinical decision workflows.
• Partner with security/compliance stakeholders to ensure test coverage supports HIPAA, SOC, and other applicable control requirements.
• Partner with product and engineering to ensure analytics/reporting correctly represents product usage, system health, and AI performance where applicable.
• Use trends and learning from incidents, defects, and telemetry to continuously improve test strategy, tooling, and release processes.

Qualifications

• Bachelor’s degree in Computer Science, Software Engineering, or equivalent practical experience.
• 6+ years in software quality engineering, test automation, or software engineering with a solid quality focus, including ownership of automation for complex systems.
• 3+ years professional software development in .NET with particular attention to test and automation frameworks.
• 3+ years of experience in front-end development and testing with JavaScript and Angular and/or React, including cross-browser testing.
• 3+ years of experience operating at a senior/principal/lead level, influencing quality strategy across multiple teams and driving outcomes through influence.
• Solid understanding of CI/CD, modern DevOps practices, and cloud-native architectures; ability to integrate quality signals into pipelines and release gates.
• Demonstrated expertise designing automation frameworks for distributed systems (APIs/services) and data-intensive platforms.
• Demonstrated excellent communication skills with a track record of translating quality risk into clear decisions for technical and non-technical stakeholders.

Preferred Qualifications

• Hands-on use of AI Coding Tools (Claude, Codex, CoPilot) and related techniques to improve testing (e.g., intelligent test selection, test generation/maintenance, failure clustering) and remediate bugs faster.
• Hands-on experience with Python and Python test frameworks.
• Experience delivering quality for AI/ML-enabled products, ideally in healthcare or another regulated domain.
• Experience with data ingestion/validation, analytics testing, and data quality observability.
• Experience validating security controls (RBAC/authorization) and supporting audit/control requirements.
• Familiarity with observability, incident learnings, and production quality signals for complex platforms.

Benefits

• Comprehensive benefits package.
• Incentive and recognition programs.
• Equity stock purchase and 401k contribution (all benefits are subject to eligibility requirements).

Application Deadline

This will be posted for a minimum of 2 business days or until a sufficient candidate pool has been collected. Job posting may come down early due to volume of applicants.