Background & Expertise
2x Microsoft MVP (AI) and Associate Consultant at Ernst & Young - building agentic AI systems, delivering hands-on Azure AI solutions, and mentoring developers globally.
I focus on Microsoft Foundry, Azure AI, agentic systems, LLMOps, AI platform engineering, and production-ready enterprise AI systems. In EY's Tech Consulting practice, I design AI-oriented enterprise systems that connect business workflows, compliance review, and applied GenAI for large-scale client engagements.
Alongside consulting work, I publish open-source AI samples, technical tutorials, and practical guidance for developers building reliable AI systems.
I thrive at the intersection of technology, architecture, and developer education - turning complex AI concepts into usable systems, reference implementations, and learning paths.
What I'm Building Toward
The engineering problems I find most interesting sit at the boundary between "agentic AI that works in a demo" and "agentic AI that holds up in production" - reliable tool use, observable failure modes, evaluation quality, cost-aware design, and deployment paths that teams can actually operate.
I'm building toward deeper ownership in applied AI engineering and AI platform architecture: Microsoft Foundry and Agent Framework delivery, LangChain and LangGraph workflows, Retrieval-Augmented Generation systems, local LLM workflows with Foundry Local and Ollama, vector database design, prompt engineering, and multi-agent orchestration that connects real enterprise data with useful outcomes.
Representative proof points include the Agent Architecture Review Sample, Microsoft ecosystem contributions such as AI Agents for Beginners, and applied privacy-first AI experiments like PrivyDoc.
Recent work has reinforced the kind of engineering I want to grow into: systems that combine AI capability with governance, audit readiness, secure cloud integrations, clear deployment paths, and enough operational resilience to survive real production pressure.
Currently Exploring
Agent reliability patterns at scale
What graceful failure looks like versus silent failure in multi-agent systems, and where shared agent context, routing, and tool orchestration become bottlenecks under real load.
Systematic LLMOps evaluation
Moving beyond manual output review toward measurable quality frameworks using RAGAS, DeepEval, custom eval pipelines, retrieval quality checks, and observability for production AI systems.
Retrieval-Augmented Generation and vector search
Designing retrieval pipelines with Azure AI Search, ChromaDB, LlamaIndex, LangChain, and vector database patterns that make answers grounded, explainable, and operationally maintainable.
Key Achievements
2x Microsoft MVP (AI)
Awarded in 2025 and 2026 - one of 33 engineers recognised globally with the Microsoft Foundry specialisation. The AI category is among the most selective within the global MVP programme. View Microsoft MVP proof.
Imagine Cup 2026 Judge
Selected as judge for Microsoft's premier global student innovation competition
EY Emerging Extraordinaire Award
Selected as one of a small number of analysts recognised organisation-wide for exceptional performance in the first year of full-time employment.
Global Outreach
21+ technical articles with ~117.4K+ views on Microsoft Tech Community
Professional Experience
EY
Technology Consulting
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Associate Consultant
September 2026 – PresentAI / Agentic Engineering / Microsoft Ecosystem
Details- ▸ Designing enterprise AI systems in EY's Tech Consulting practice, focused on agentic pipelines, GenAI compliance review, and CRM-integrated analytics for large-scale client engagements
- ▸ Driving deeper AI and automation engineering across Microsoft technologies and applied enterprise delivery.
Promoted: Senior Analyst → Associate Consultant (September 2026)
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Senior Analyst
2025 – September 2026Technology Consulting / Power Platform / Client Delivery
Details- ▸ Owned the OE module end-to-end across claims, approval, and validation streams, translating cross-functional business and compliance requirements into production-ready systems
- ▸ Partnered with business, GRC, and client stakeholders to deliver systems designed for operational accuracy, regional scale, and long-term maintainability
🏆 EY Emerging Extraordinaire Award - 2025
Selected as one of a small number of analysts recognised organisation-wide for exceptional performance, technical innovation, and measurable contribution to client outcomes. Awarded in the first year of full-time employment at Ernst & Young.
Data Analyst Intern
Ernst & Young (EY)
- ▸ Built synthetic time-series pipelines using Synthetify, improving model reliability by 40%
- ▸ Developed a Questro-based chatbot for contextual document insights, accelerating analysis by ~90%
Data Analyst Intern
Ernst & Young (EY)
- ▸ Improved solar energy forecasting accuracy by 30% using ML models on weather data
- ▸ Optimized grid integration and resource allocation, supporting renewable energy adoption
Certifications
Microsoft Azure AI Apps and Agents Developer Associate (AI-103)
Microsoft Certified
Azure AI Fundamentals (AI-900)
Microsoft Certified
AWS Certified Cloud Practitioner
Amazon Web Services
Academic Background
B.Tech in Computer Science
The NorthCap University, Gurugram
Specialization: Artificial Intelligence & Machine Learning
Class 12th (CBSE)
St. Xavier's Sr. Sec School, Haryana
Class 10th (CBSE)
St. Xavier's Sr. Sec School, Haryana