Anurag Gupta
Senior Manager Quality Engineering @Signify Health
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WORK HISTORY
Senior Manager Quality Engineering @Signify Health
Led organization-wide adoption of Model Context Protocol (MCP), training teams on AI-assisted development using Cursor Created and implemented specialized MCPs for multiple platforms Developed RAG-based chatbot solution for customer care Engineered synthetic data generation solutions ensuring robust test coverage while maintaining data privacy compliance Implemented Team Testing Model to enhance collaboration and shared responsibility for quality across development and QE teams Established DORA metrics tracking and improvement initiatives, leading to reduced lead times and improved deployment frequency Led and mentored team of 9 Quality Engineers, successfully managing performance improvement plans and complex team dynamics Created standardized CI/CD templates integrating test automation with Zephyr and Slack notifications Successfully orchestrated GitHub migration for all test automation frameworks Successfully migrated legacy Karate and Cypress frameworks to centralized C# framework, improving maintenance efficiency by 30% Established centralized patch automation pipeline for production deployments, ensuring comprehensive endpoint validation
EDUCATION
MIT Professional Education
Applied Agentic AI for Organizational Transformation, Artificial Intelligence
University of Rajasthan
Bachelor of Engineering - BE, Information Technology
ABOUT ANURAG GUPTA
Over 15+ years of experience spanning software engineering, QA automation, and AI-driven platform development, with a strong evolution from hands-on testing to leading large-scale, intelligent systems and engineering organizations. Currently focused on building agentic AI solutions, synthetic data platforms, and scalable cloud-native architectures that drive measurable business impact. Proven track record of delivering high-impact systems, including an autonomous AI-based RPA replacement (ProConsult AI Bot) achieving 300% faster execution and 95% lower maintenance, and a Kubernetes-native synthetic data platform (DataGenie) generating millions of HIPAA-compliant records while saving $2.5M annually. Extensive experience in defining AI strategy, guiding teams on model selection for cost-performance optimization, and enabling adoption through technical leadership and training sessions. Strong background in observability and reliability engineering using OpenTelemetry, New Relic, Grafana, Elastic, Phoenix, and Arize. Currently leading and mentoring 16+ engineers (30+ org-wide), driving technical direction for AI and platform initiatives, managing $2M+ budgets, and delivering 30% cost optimization with 40% improved delivery predictability.Key strengths and experience: AI/Agentic Systems: Built LLM-powered autonomous agents capable of UI navigation using screenshot reasoning and browser automation. Synthetic Data Platforms: Designed HIPAA-compliant, scalable data generation systems using Synthea, LLM schema intelligence, and Kubernetes. Engineering Leadership: Built and scaled high-performing teams, led cross-functional initiatives, and drove technical strategy for AI-first systems. Observability & Reliability: Implemented end-to-end monitoring, logging, and tracing frameworks to improve system performance and incident response. Cost Optimization: Reduced infrastructure and API costs through in-house platforms (e.g, address generation system replacing Google APIs) and efficient cloud architecture. Full-Stack & Cloud: Experience across Python, FastAPI, Node.js, TypeScript, AWS, Kubernetes, CI/CD, and distributed systems. Earlier in my career, built deep expertise in QA automation, Selenium, API testing, mobile (iOS/Android), and DevOps practices, forming a strong foundation for delivering high-quality, scalable systems. Passionate about leveraging AI to transform traditional workflows, improve efficiency, and build next-generation intelligent platforms.
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