Senior Quality Engineer – Agentic AI & Autonomous Testing

Job Description: Senior Quality Engineer – Agentic AI & Autonomous Testing Locations: Jaipur, Noida, Gurgaon, Pune, Bengaluru, Hyderabad Duration: 3-6 Months Contract with possible extension Experience: 10+ Years Role Overview We are seeking a Senior Quality Engineer (QE) with deep hands-on expertise in Agentic AI and Autonomous Testing systems to lead the next generation of quality engineering. This role goes beyond traditional automation to design, build, and operate intelligent QA agents capable of independently planning, executing, analyzing, and optimizing testing workflows across enterprise applications. The ideal candidate will combine strong QE foundations, AI/ML understanding, and engineering rigor to build self-learning test ecosystems that improve coverage, reduce manual effort, and enable continuous quality at scale. This role is critical for establishing an AI-first QE capability where agents act as autonomous testers, quality guardians, and optimization engines embedded across the SDLC. --- Key Responsibilities 1. Agentic AI Testing Architecture & Development • Design and build autonomous QA agents capable of: • Test discovery, generation, execution, and maintenance • Failure diagnosis and root cause analysis • Self-healing and adaptive test strategies • Develop agent architectures using LLMs, workflows, and orchestration layers (e.g., sense → decide → act → learn loop) • Define agent goals, constraints, and reasoning logic to enable independent decision-making in testing workflows • Implement multi-agent ecosystems (test generation agents, validation agents, monitoring agents) --- 2. Autonomous Test Strategy & Execution • Build end-to-end autonomous testing frameworks that: • Generate test cases from requirements, APIs, and production data • Explore systems dynamically to uncover edge cases and untested paths • Maintain and optimize test suites through continuous learning • Design behavior-driven evaluation systems (not just assertion-based testing) • Implement AI-driven regression, exploratory, and risk-based testing models • Enable self-healing and adaptive execution to reduce maintenance overhead --- 3. AI Validation, Evaluation & Observability • Build evaluation frameworks for non-deterministic AI systems: • Behavior-based validation (vs exact output matching) • LLM-as-judge scoring frameworks • Semantic and structured validation approaches • Define and monitor AI-specific quality metrics: • Accuracy, reliability, hallucination rates, drift, safety • Implement continuous validation and observability pipelines • Establish governance controls, auditability, and quality gates for AI-driven testing --- 4. QE Platform Engineering & Integration • Integrate agentic testing into CI/CD pipelines and DevOps workflows • Build scalable AI-enabled automation frameworks across: • Web, mobile, API, and backend systems • Enable closed-loop learning systems where agents improve based on execution data • Collaborate with engineering to embed quality as code / quality as platform --- 5. AI-Driven Quality Transformation • Drive transition from: • Script-based automation → agent-based autonomous testing • Manual validation → intelligent quality orchestration • Define enterprise QE strategy for AI adoption (agent-first testing model) • Introduce capabilities such as: • AI-generated test assets • Predictive defect detection • Automated failure triage and clustering • Act as SME for Agentic QA practices, tools, and frameworks --- 6.

Collaboration & Stakeholder Engagement • Partner with: • Engineering, Product, Data, Architecture, Business • Translate business requirements into autonomous test strategies • Drive cross-functional alignment on quality, risk, and governance • Mentor teams on AI-driven QA practices and agent development --- Required Skills & Experience Core QE & Engineering • 10–12+ years in Quality Engineering / Test Automation • Deep expertise in: • Automation frameworks (Selenium,WebdriverIO, Maestro, Cypress, etc.) • API testing, performance testing, and integration validation • Strong programming skills (Python, Java, JavaScript, or C#) --- Agentic AI & Autonomous Testing (Must-Have) • Proven experience building or working with: • AI testing agents / autonomous testing systems • LLM-based workflows, prompt engineering, and reasoning systems • Hands-on with: • AI-driven test generation, self-healing frameworks, or adaptive testing • Understanding of agent capabilities: • Perception, reasoning, planning, execution, feedback loops --- AI/ML & Data Competency • Working knowledge of: • Machine learning concepts, NLP, embeddings, RAG • Experience designing: • Evaluation metrics and scoring systems for AI outputs • Familiarity with: • Data pipelines, model validation, and drift detection --- Modern QE & DevOps • Experience integrating testing into: • CI/CD pipelines (Jenkins, GitHub Actions, Azure DevOps) • Strong understanding of: • Microservices, APIs, distributed systems • Exposure to: • Cloud platforms (AWS, Azure, GCP) --- Advanced Skills (Highly Preferred) • Experience with Copilot Studio / AI agent platforms • Multi-agent system design and orchestration • Experience in regulated environments (banking, fintech, compliance-heavy systems) • Knowledge of Responsible AI / AI governance frameworks --- Behavioral & Leadership Competencies • Strong systems thinking and problem-solving ability • Ability to work in non-deterministic, probabilistic environments • High ownership of quality, risk, and delivery outcomes • Strong stakeholder communication (engineering + business) • Ability to mentor and scale AI-first QE practices