Headline

AI/ML Testing/QA Manager | GenAI, Agentic AI Testing |LLM & RAG Testing | Playwright Automation | Prompt Engineering Validation | AWS | Accessibility Testing |Shift-Left Quality for Enterprise AI |Serving Notice Period |

About

With extensive experience of 17 Years in QA Engineering, Quality Engineering, Automation Architecture, and AI-driven Engineering Systems. As a Senior Test Architect and the founder of HAI — Himanshu AI, I focus on helping engineers transition from traditional Automation Testing into Agentic AI, GenAI, AI Agents, MCP, RAG, and next-generation AI systems. My work spans large-scale automation ecosystems, enterprise QA modernization, AI-augmented workflows, and intelligent testing strategies across multiple Fortune 500 product lines. My technical expertise includes Playwright, Java, TS, Python, Prompts Testing, LLM Testing, RAG Testing, MCP Testing, GEN-AI Testing, Agentic AI Testing, Autonomous QA/ Testing, ML/AI Models Testing, AWS, API Testing, AI-powered automation frameworks, CI/CD pipelines, enterprise test architecture, and scalable automation ecosystems. I am actively building high-authority AI learning resources, roadmaps, SDETs, QA professionals, and engineers entering the AI era. My expertise spans web, API, mobile, microservices, distributed systems, cloud platforms, and modern AI applications. I have hands-on experience designing enterprise-grade automation frameworks and quality platforms using Playwright, Cypress, Appium, Robot Framework, API Testing, Docker, AWS, Jenkins & GitHub Actions. I am actively Working & Exploring and validating emerging AI technologies, including (Tech Stack) ✔ LLMs (OpenAI, Claude, Gemini, GEN-AI & Llama) ✔ AI Agents & Agentic Frameworks ✔ MCP (Model Context Protocol) ✔ RAG Systems & Vector Databases ✔ AI Evaluation Frameworks ✔ Prompt Engineering ✔ AI Observability (Grafana, Arize AI, Evidently AI, Fiddler AI, Datadog, New Relic, Dynatrace, Prometheus) ✔ AI Automation Tools (Applitools, TestMu, Functionize, MABL, TOSCA AI, ACCELQ, Testim & TestRigor) ✔ Cloud & DevOps Technologies ✔ Productivity & Engineering Tools Through hands-on working & Experimentation, real-world implementation, and technical research, I share practical insights, tutorials, architecture breakdowns, framework design concepts, testing strategies, AI evaluation techniques, and engineering best practices for QA Engineers, SDETs, Developers, DevOps Engineers, and AI Engineers. My current focus areas include: • AI Testing & Evaluation • LLM Testing & Hallucination Detection • RAG Validation & Evaluation • AI Agent Testing • MCP & Agentic Workflows • Automation Framework Architecture • CI/CD & DevOps • Software Quality Engineering • System Design for Engineers • Modern AI Engineering Practices

Location

Greater Bengaluru Area

AI stack

deepseek

github copilot

grok

hugging face

langchain

langgraph

Work experience

Manager-AI/ML Testing, GEN-AI Testing, Playwright, MCP, API Testing at BlueCross BlueShield of South Carolina, Apr 2025 - Present · 1 yr 5 mos, India, Lead end-to-end delivery of AI Data Assurance programs. Drive delivery governance, quality metrics, executive reporting, and Agile/Hybrid delivery excellence. Quality Engineering, AI Assurance & Governance Define quality strategies, testing frameworks, and assurance processes for AI/ML, GenAI, AI data assurance, analytics, and BI platforms. Govern end-to-end validation, release readiness, and quality gates. Lead testing and validation of data platforms, pipelines, analytics solutions, BI platforms and AI-ready datasets. Implement AI Data Harness Assurance across data pipelines, RAG systems, vector stores, and AI workflows. Drive AI Data Outcome Assurance by evaluating AI output quality, reliability, explainability, and business alignment. Support Responsible AI, AI Governance, and Model Assurance initiatives. Automation, Client Orientation & Team Leadership Build automation frameworks for AI Data Assurance, BI assurance and continuous quality monitoring. Define and drive end-to-end test strategy and governance for AI systems Lead and mentor QE teams delivering AI testing engagements Oversee data validation, model evaluation, anomaly detection, and statistical analysis Ensure AI systems meet functional, performance, ethical, and responsible AI requirements Establish metrics and KPIs to measure AI system effectiveness and quality Manage stakeholder communication across clients and internal teams Plan and forecast resource requirements for AI testing engagements Drive adoption of best practices, tools, and frameworks across AI testing delivery Identify risks in AI models and define mitigation strategies Prepare and present testing reports, risks, and progress updates to stakeholders Maintain documentation of testing processes, results, and learnings

Senior QA/Test Manager-AI/ML Testing & GEN-AI Testing at NTT DATA, Aug 2022 - Feb 2025 · 2 yrs 7 mos, Andhra Pradesh, India, Leading, Working and Manage the AI-Testing/QA team, establishing AI-Test strategy, processes, and governance. Strategized and created ML Model Automation pipelines and reduced the regression AI-Driven QA Strategy & Architecture: Design and implement AI-powered QA frameworks integrating capabilities such as self-healing automation, intelligent defect prediction, test case generation, and root cause analysis. Define and execute the AI enablement roadmap for QA practices, leveraging LLMs, ML models, and automation accelerators. Created QA Agent and GenAI Application Test Automation. Develop Agent-based GenAI applications using frameworks such as LangChain, LlamaIndex, or Semantic Kernel. Enable multi-agent collaboration for test generation, failure triage, and defect clustering. AI Application Integration & Automation: Build and integrate GenAI applications with GitHub Copilot, CI/CD pipelines, and test automation frameworks. Implement AI-based copilots to assist test engineers with code suggestions, scenario design, and defect classification. Host and deploy AI applications on cloud (Azure/AWS/GCP) or on-premise intranet environments, ensuring security and compliance. Develop AI/ML components using Python, JavaScript, or Java, integrating APIs from OpenAI, Gemini, Claude, or Azure OpenAI Service. Create and fine-tune LLM prompts and workflows for test artifact generation, requirement understanding, and automation script synthesis Working on AI-based QA solutions — self-healing, test generation, or intelligent analytics Cut test design effort by 50% by introducing AI-assisted workflows and reusable strategy templates . Testing and Developing Agent-based GenAI apps using LangChain, LlamaIndex, AutoGen and CrewAI. Implementing AI-driven QA accelerators or GenAI copilots within enterprise testing environments End to End test automation for LLM/Agentic AI systems with AI technologies CLIENT-PROJECTS: HSBC, WESTPAC, Pfizer and MANKIND PHARMA

Sr. Lead-Software QA at Freyr Solutions, Mar 2020 - Aug 2022 · 2 yrs 6 mos, Hyderabad, Telangana, India, Project: INTAS PHARMA: Fr. IMPACT Test Lead | Automation Strategy | BDD | CI/CD | Agile Delivery Led end-to-end QA and Automation strategy for a multi-state legal digitization platform, owning the full test lifecycle from framework design to delivery. Specialized in Java, API Testing, Appium, Selenium WebDriver, Cucumber BDD, and Agile-aligned test governance across cross-functional engineering teams. Worked in automation testing & debugging using tools like POSTMAN, SOAP UI, REST Assured. Achievements 1. POS & BDD automation framework Built and governed a production-grade BDD Automation Framework using Cucumber, Selenium WebDriver, and Java — enabling Gherkin-based living documentation and accelerating test authoring across QA and business teams. 2. API test coverage & regression Designed and implemented comprehensive API test coverage and regression suites using Java-based tooling, ensuring stability and reliability of critical legal management workflows. 3. CI/CD pipeline integration Integrated Selenium + Cucumber BDD automation suites into CI/CD pipelines, enabling continuous test execution and faster feedback loops aligned with Agile sprint cycles. 4. Cross-functional team leadership Managed and mentored cross-functional QA and engineering teams, embedding Shift-Left testing and BDD practices across Agile squads to improve collaboration between developers, testers, and product owners. 5. On-time delivery — 20% ahead of schedule Delivered the Fre iMPACT project 30% ahead of schedule by streamlining test planning, parallel execution, and early defect detection through automation-first strategy. 6. Client satisfaction — 80% improvement Improved client satisfaction scores by 80% through structured QA governance, transparent reporting, and consistent delivery quality across all release milestones. 7. Worked on E2E QA Project/Product Management from QA/Testing standpoint. CLIENTS: INTAS PHARMA, CIPLA, RANBOXY and J&J

QA Manager & Project Management-Testing Practice at PFS, Sep 2015 - Apr 2020 · 4 yrs 8 mos, Greater Bengaluru Area, Design, implement and manage a thorough Quality Assurance process for the company, including identification of the technical resources needed to perform QA on all software development products. Participate in regular meetings with Engineering and Development (including daily scrums) to represent and prioritize QA requirements. Build automation testing strategies and frameworks. Led the QA lifecycle for large-scale cloud migrations and feature releases, balancing manual and automated efforts. CI/CD Integration : Seamlessly integrate data quality gates into the CI/CD pipeline to support agile delivery in a cloud-native environment. Assist in coordinating functional, data, and integration testing streams Monitors and report UAT progress, risks, and quality metrics to IT project teams and senior leadership Provides leadership, mentorship, and performance management for UAT staff, including testers and business analysts. Serves as the point of escalation for UAT-related issues and decision-making Continuously assess and improve UAT processes, toolsets, and team capabilities. Transformation & Thought Leadership -Introduce and scale AI/ML, GenAI, and autonomous testing techniques into the testing lifecycle. Monitor Test metrics (test coverage, defect leakage, automation ROI) and continuously improve test effectiveness and efficiency. Ensure UAT activities align with Agile/iterative delivery models and overall release management processes Partner with Product, Engineering, QA, Operations, Compliance, and Risk teams to ensure business readiness Define and execute the AI enablement roadmap for QA practices, leveraging LLMs, ML models, and automation accelerators Build and integrate Gen-AI applications with GitHub Copilot, CI/CD pipelines, and test automation frameworks CLIENT-PROJECTS: Dallas-Cowboys, EMERSON, and P&G

Team Lead-CSV and Validation at ArisGlobal, Nov 2012 - Aug 2015 · 2 yrs 10 mos, Bengaluru, Karnataka, India, Own and define the Salesforce testing and quality assurance strategy, covering functional, regression, integration, API, UAT, and end-to-end testing. Oversee regression testing execution, parallel test runs, and environment-specific validation across sandboxes and production Support UAT coordination with business stakeholders and validate production deployments. Manage all Verification and Validation activities and deliverables for New Product Development and sustaining products in accordance with Client’s Quality Management System and applicable medical-device regulations and standards. Design patterns for implementation with Agentic Harness Define and implement test strategies, plans, and test cases aligned with business and technical requirements Improve QA processes and collaborate with development, product management, and DevOps Oversee the implementation and maintenance of automation frameworks and tools Worked on manual and automation testing methodologies and tools (Selenium, TestNG, JUnit, API Testing, Cucumber, Appium and Postman). Architect and maintain reusable automation frameworks for both traditional and AI-driven applications, integrated with CI/CD pipelines Design, develop, and maintain standard and ad-hoc reports tailored to business needs. Implement automated reporting processes to reduce manual effort and improve timeliness. Build reusable automation frameworks for AI testing integrated with CI/CD pipelines PROJECTS & CLIENTS WORKED: ABOTT, ROCHE, GLENMARK and LUPIN PHARMA

Team Lead at SLK, Jul 2011 - Aug 2012 · 1 y 1 mo, Bangalore, Worked as a Team Lead for 5/3 Bank USA client on QE Applications and Played as a Scrum Master too

Consultant at Polaris Software, Jan 2008 - Jul 2011 · 3 y 6 mo, Hyderabad, Worked as a Consultant for CITIGROUP client . Working on SIT Testing, UAT , QTP Automation ,BI Reports Testing, Agile along with client facing.

Education

Master of Business Administration - MBA, Information Technology Project Management, NIBM Institute

B.Tech, Information Technology, University of Madras