Quality Engineer - GenAI and Data Platforms

Role

Quality Engineer responsible for validating Generative AI-enabled web applications and their data/analytics backbone. The role performs end-to-end testing across .NET APIs, React frontends, Databricks workflows, and Azure Data Factory pipelines to ensure quality, safety, reliability, and compliance of AI-driven features and data outputs.

Key Responsibilities

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 hallucinations and incorrect reasoning.

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, schemas, and downstream interactions.
• Support API automation in CI/CD pipelines.

Frontend Testing (React)

• Test React web applications for functional correctness, UI behavior, 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 batch and incremental loads; verify transformations and schema changes.
• Perform end-to-end data flow validation from ingestion to consumption.

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 model/prompt/configuration 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, auditability, and traceability of AI outputs.

AI Builder Responsibilities

• Use GenAI tools (Copilot, Claude, Gemini) to ideate, prototype, and implement features.
• Apply vibe coding techniques to maintain clean, expressive, and AI-augmented codebases.
• Develop internal tools and scripts using AI to automate repetitive tasks and improve productivity.

Requirements

Required Qualifications

• Graduate degree or equivalent experience; Bachelor’s in Computer Science or related discipline preferred.
• 2+ years of hands-on experience as a Quality Engineer / Software Tester / QA Engineer.
• Solid experience in manual and automated testing, test planning, defect management, and root-cause analysis.
• Experience working in Agile/Scrum teams.

Backend & Frontend

• Experience testing .NET / REST APIs (Postman or automation frameworks) and React applications.
• Good understanding of web technologies (HTTP, JSON, browser behavior).

Data & Cloud

• Experience with Azure Data Factory (ADF) pipelines and Databricks (running notebooks, validating outputs).
• Understanding of data warehousing/analytics concepts and solid SQL skills for data validation.

GenAI & AI Testing

• Understanding of Generative AI and LLM-based systems, prompt-based interactions, non-deterministic outputs, and RAG-style workflows.
• Ability to evaluate AI quality beyond simple pass/fail outcomes.

Preferred

• Python or scripting skills for test automation.
• Experience testing AI/ML or analytics platforms.
• CI/CD tools and pipeline-based testing experience; exposure to monitoring and production validation of AI systems.

Soft Skills

• Strong analytical and problem-solving skills, ability to articulate AI quality risks, collaboration with developers/data engineers/AI engineers, high ownership, and attention to detail.