Lead Consultant - QA(AI) Engineer
Delphi Consulting India
Information Technology & Services · 201-500 employees
About the role
The Lead Consultant will own end-to-end quality assurance for AI and Generative AI engagements, including test strategy, planning, and execution. They will lead and mentor QA pods while collaborating with engineering, AI/ML, and business teams to ensure production-grade quality outcomes.
What they look for
Requirements
Candidates must have 10–15 years of experience in Software QA with at least 3–4 years in a leadership role. Hands-on experience testing AI/GenAI applications in regulated industries like Finance, Healthcare, or Insurance is required.
Benefits
Full description
Join Delphi - Where Innovation meets transformation
At Delphi, we believe in creating an environment where our people thrive. Our hybrid work model empowers you to choose where you work—whether it's from the office, your home, or a mix of both—so you can prioritize what matters most. We are committed to supporting your personal goals, family, and overall well-being while driving transformative results for our clients.
We welcome exceptional talent from anywhere across the globe. Interviews and onboarding are conducted virtually, reflecting our digital-first mindset.
Rooted in the region, we specialize in delivering tailored, impactful solutions in Data, Advanced Analytics and AI, Infrastructure, Cloud Security, and Application Modernization. Whether it’s enabling predictive analytics, transforming operations with automation, or driving customer engagement with intelligent platforms, we are the trusted partner for organizations ready to embrace a smarter, more efficient future.
We are looking for a hands-on Senior QA Consultant to lead end-to-end testing of AI and Generative AI applications across enterprise environments. This role combines strong expertise in traditional QA engineering with modern AI evaluation and validation practices. The ideal candidate will drive quality assurance initiatives for RAG pipelines, multi-agent systems, OCR and Speech-to-Text solutions while ensuring production grade quality outcomes in regulated industries such as Finance, Healthcare, and Insurance. The successful candidate will lead a small QA pod, collaborate closely with engineering, AI/ML, product, and business teams, and act as the client-facing QA owner for enterprise AI engagements. This role requires strong technical leadership, automation expertise, AI evaluation capabilities, and excellent stakeholder management skills. Experience Requirements
- 10–15 years of experience in Software QA / Test Engineering
- 3–4 years of experience leading QA teams or delivery pods
- Hands-on experience testing AI / GenAI applications in production environments
- Experience working within regulated domains such as Finance, Healthcare,
Insurance, or similar industries Key Responsibilities Quality Engineering & Delivery
- Own end-to-end quality assurance for AI/GenAI engagements including test strategy,
planning, execution, defect management, reporting, and exit criteria
- Lead and mentor QA pods of 3–6 engineers across automation frameworks, AI testing
practices, and delivery execution
- Design and execute functional, API, backend, integration, regression, performance,
and AI evaluation test cases
- Build and maintain scalable automation frameworks for Web, Mobile, and API testing
- Drive continuous quality improvements through reusable accelerators, frameworks,
datasets, and evaluation tools AI Application Testing & Evaluation
- Define AI-specific test coverage including prompt validation, hallucination detection,
groundedness checks, retrieval quality, tool-call correctness, latency, bias, and safety testing
- Design and execute testing strategies for RAG architectures, multi-agent workflows,
OCR systems, and Speech-to-Text applications
- Build synthetic datasets covering edge cases, adversarial scenarios, persona-based
workflows, and multimodal inputs
- Implement LLM-as-a-Judge evaluation pipelines using customizable scoring rubrics
and multi-model evaluations
- Produce detailed AI quality scorecards and benchmarking reports across accuracy,
relevancy, faithfulness, and safety metrics Automation, CI/CD & Tooling
- Integrate AI evaluation and automation testing into Jenkins and Azure DevOps CI/CD
pipelines
- Build regression dashboards, quality gates, and automated reporting frameworks
- Perform API testing, backend validation, database testing, and event-driven workflow
validation
- Conduct load and performance testing using modern performance engineering tools
- Support cross-browser, parallel, and scalable automation execution environments
Client & Stakeholder Management
- Act as the client-facing QA lead for enterprise engagements
- Conduct quality reviews, risk assessments, and stakeholder reporting sessions
- Translate technical quality metrics into business-focused outcomes and
recommendations
- Collaborate with engineering, AI/ML, product, and leadership teams to ensure
successful delivery outcomes Required Technical Skills - Core QA & Automation
- Functional Testing, Exploratory Testing, Requirements Traceability, and Test Design
Techniques
- API Testing using REST, GraphQL, Postman/Newman, RestAssured, and Requests
- Backend and Database Testing across SQL Server, MySQL, Oracle, PostgreSQL, and
ETL/Data Pipelines
- Automation Frameworks using Selenium, Playwright, PyTest, and Appium
- Performance Testing using JMeter, k6, or Locust
Programming & Development -
- Strong programming expertise in Python or Java
- Knowledge of OOP concepts, design patterns, data structures, and unit testing
frameworks
- Ability to build utilities, custom assertions, CLI tools, and reusable automation
components AI & Generative AI Testing
- Hands-on experience testing AI/GenAI applications in enterprise environments
- Knowledge of LLM platforms including OpenAI, Anthropic, Azure OpenAI, AWS
Bedrock, and Vertex AI
- Experience with orchestration frameworks such as LangChain, LlamaIndex, and
Semantic Kernel
- Understanding of multi-agent systems, memory handling, routing, tool calling, and
guardrails
- Expertise in RAG evaluation, vector databases, embeddings, retrieval quality, and
hallucination testing
- Familiarity with AI evaluation platforms such as RAGAS, DeepEval, Galileo, Arize
Phoenix, Patronus, Okareo, or similar tools
- Experience validating OCR systems and Speech-to-Text solutions using WER/CER and
degradation testing methodologies Build, DevOps & Platforms
- Azure DevOps, Jenkins, JIRA/Xray or Zephyr, GitHub/GitLab/Bitbucket
- CI/CD pipelines, regression dashboards, and quality gate implementation
- Exposure to Power Platform tools including Power Apps, Power BI, and Power
Automate is a plus Domain & Compliance Expertise
- Experience working in regulated industry environments such as Banking, Financial
Services, Healthcare, Insurance, or Life Sciences
- Understanding of compliance requirements including data privacy, PII/PHI handling,
explainability, and AI governance practices Behavioral & Consulting Skills
- Strong leadership and mentoring capabilities
- Excellent verbal and written communication skills
- Client-centric and solution-oriented mindset
- Strong stakeholder management and collaboration abilities
- Ownership mindset with proactive problem-solving approach
- Ability to work effectively in fast-paced consulting environments
- Continuous learner with strong interest in emerging AI testing methodologies and
tools Preferred Qualifications
- Bachelor’s degree in Computer Science, Engineering, or a related field
- Master’s degree preferred
- Certifications such as ISTQB Advanced, Certified Agile Tester, AWS/Azure AI
Certifications, or equivalent
- Experience with adversarial testing and responsible AI frameworks such as NIST AI
RMF or ISO 42001
- Exposure to MLOps / LLMOps observability and production monitoring
- Contributions to QA or AI communities through blogs, speaking sessions, or open
source initiatives What Success Looks Like
- High-quality delivery outcomes with measurable reduction in defect leakage
- Successful implementation of reusable AI QA accelerators and automation
frameworks
- Strong stakeholder and client feedback across engagements
- Growth and technical enablement of QA pod members under leadership
- Continuous improvement of AI testing practices, evaluation frameworks, and delivery
standards
What we offer
At Delphi, we are dedicated to creating an environment where you can thrive, both professionally and personally. Our competitive compensation package, performance-based incentives, and health benefits are designed to ensure you're well-supported. We believe in your continuous growth and offer company-sponsored certifications, training programs, and skill-building opportunities to help you succeed.
We foster a culture of inclusivity and support, with remote work options and a fully supported work-from-home setup to ensure your comfort and productivity. Our positive and inclusive culture includes team activities, wellness and mental health programs to ensure you feel supported.
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