Quality Engineer - GenAI and Data Platforms

Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together.

Overview We are looking for a Quality Engineer to work on Generative AI-enabled web applications, built on .NET APIs and React frontend, with a solid data and analytics backbone. This role is critical in ensuring the quality, reliability, safety, and compliance of AI‑driven features, data pipelines, and analytical insights. The engineer will actively test GenAI use cases, APIs, UI components, and data pipelines, and should be comfortable running and validating Databricks and Azure Data Factory (ADF) pipelines as part of end‑to‑end testing. With every role in the company, each position has a requirement for building quality into every output. The Technology Quality Function is reserved for those positions where Quality is the primary objective of the work delivered. Technology Quality roles will cover all primary quality activity across all technology functions that ensure we deliver high quality products and services. These roles include, but are not limited to, strategy, planning, standards, process, policy, tools, engineering, assurance, management, metrics, research and development, automation, data preparation, maintenance, new development, operations and delivery.

Analyzes and investigates Provides explanations and interpretations within area of expertise GenAI and Application Quality Validate Generative AI features such as chat interfaces, summarization, insights, and recommendations Perform prompt and response testing, including edge cases, ambiguity handling, and failure scenarios Test AI behavior for accuracy, relevance, consistency, and safety Identify and report issues related to hallucinations, incorrect reasoning, or incomplete responses. API and Backend Testing (.NET) Test .NET‑based REST APIs for functionality, validation, error handling, performance, and security Perform integration testing between APIs and GenAI services/models Validate payloads, response schemas, and downstream system interactions Support API automation as part of CI/CD pipelines Frontend Testing (React) Test React‑based web applications for: Functional correctness UI behavior and validations Cross‑browser and responsive behavior Validate AI‑driven UI components such as chat windows, dashboards, and analytics views Data and Analytics‑Centric Testing Validate data accuracy, completeness, and consistency across analytics dashboards and reports Test business logic and calculations used in analytical outputs Validate data used by AI models and retrieval systems Databricks and ADF Pipeline Validation Run and validate Databricks notebooks and jobs as part of test execution Trigger, monitor, and validate Azure Data Factory pipelines for both batch and incremental loads Verify data transformations, schema changes, and quality checks Perform end‑to‑end data flow validation from ingestion to consumption layers Automation and Quality Engineering Develop and execute automated tests for APIs, UI, and data validations where applicable Design reusable test utilities for AI and data validation Support regression testing for AI model, prompt, configuration, or pipeline changes Compliance and Responsible AI Validate applications for data privacy, PHI/PII handling, and access controls Support Responsible AI and governance checks, including fairness, bias, and safe usage validations Ensure auditability and traceability of test results