Headline

GenAI & AI | Data Science | Driving Innovation Through Agentic Architectures, ML, and Business Intelligence

About

I am a Senior Technical Architect with 14 years of experience delivering enterprise-scale AI and data solutions. I specialize in building production-grade GenAI systems, leading presales engagements, and collaborating with global cloud partners to bring the latest technologies into enterprise environments. My core expertise lies in designing multi-agent architectures using LangChain, Autogen, Semantic Kernel, and Azure AI Foundry SDKs. I develop context-aware agents and microservices using FastAPI, integrated with Model Context Protocol (MCP) and Agent-to-Agent (A2A) communication. These systems are deployed on Azure (AKS, VMs, Blob Storage) with SSE-based logging and full observability. I work closely with Microsoft and Google product teams to adopt and shape emerging capabilities across GPT-4.0, retrieval-augmented generation (RAG), and declarative agent orchestration via Copilot Studio and Vertex AI extensions. I also build LLM-enhanced VSCode extensions to automate code generation, review workflows, and improve developer productivity. In parallel, I drive presales consulting engagements—translating business problems into AI solution blueprints, leading client workshops, shaping technology roadmaps, and delivering high-impact demos and proposals across verticals. Technically, I’m proficient across Azure Databricks, ML Studio, Stream Analytics, Data Explorer, Power BI, and Python-based ML/ETL pipelines. Architecturally, I focus on modularity, memory persistence, prompt chaining, tool invocation, and real-time orchestration. I lead GenAI adoption through Center of Excellence programs, reusable framework design, security governance, and team capability uplift—delivering trusted, future-ready AI solutions for Fortune 500 clients across tech, BFSI, retail, and manufacturing sectors.

Location

India

AI stack

codex

cursor

opencode

Work experience

Senior Technical GenAI/AI Architect at Coforge, Dec 2024 - Present · 1 yr 9 mos, As a Senior Architect and CoE Lead, I have driven AI and developer productivity initiatives across enterprise environments, aligning solution architecture with organizational goals. Core Responsibilities & Impact Areas: Enterprise GenAI Architecture & Delivery Designed and implemented modular, production-grade GenAI agents and microservices. Leveraged Azure OpenAI & other LLMs for intelligent task automation, natural language understanding, and decision support. Used LangChain, LLM orchestration frameworks, and Azure AI Foundry SDKs for rapid GenAI solution development. Built and deployed microservices using FastAPI, adhering to MCP (Microsoft Compliant Packaging) standards with A2A (Agent-to-Agent) protocol support. Developer Tooling & Productivity Developed tools and extensions to enhance code quality, reduce cycle time, and embed LLM-powered assistance in developer workflows. Built VSCode extensions, integrated GitHub Actions, and enabled auto-suggestions, code review automation, and prompt engineering pipelines. Copilot Studio & Declarative Agent Design Delivered declarative agents using Microsoft Copilot Studio with reusable prompt templates and integrated API connectors (Graph API, SharePoint, etc.). Standardized agent configuration and behavior using declarative schemas and plugin-style architecture. Cloud-Native Engineering & Deployment Architected solutions for Azure Kubernetes Service (AKS), Azure Virtual Machines, and Azure Blob Storage. Implemented Server-Sent Events (SSE) for real-time logging and telemetry. Ensured full observability, traceability, and modular deployment across agent pipelines. CoE Leadership & Strategic Enablement Led multiple strategic initiatives under the GenAI Center of Excellence, setting best practices for reusability, modularity, and secure deployment. Established frameworks for agent design lifecycle, lineage tracking, and integration with internal platforms and developer ecosystems.

GenAI Consulting & Client Engagement- Retail & CPG (Assoc Director) at Fractal, Feb 2024 - Nov 2024 · 10 mos, Strategic Leadership: Directed AI and Data Science initiatives across multiple domains, ensuring alignment with long-term business objectives. Led large-scale AI engagements, defining the roadmap and spearheading high-impact projects that deliver measurable business value. AI Solution Architecture & Innovation: Architected cutting-edge Generative AI and Machine Learning solutions, leveraging advanced tools like LangChain, LLamaIndex, and CrewAI. Drove end-to-end solutioning from concept through Proof of Value (POV), delivering high-value AI strategies that solved complex client challenges. Client Engagement & Business Development: Engaged directly with C-suite clients, understanding their business challenges and shaping AI strategies that drive innovation and operational efficiency. Played a critical role in presales and business development, contributing to revenue growth through tailored AI solutions and strategic client partnerships. Cloud & AI Platforms: Leveraged deep expertise in deploying AI and Machine Learning solutions on Azure, AWS, and Google Cloud, ensuring scalability, cost efficiency, and seamless integration with client environments. Leadership & Organizational Growth: Led cross-functional teams, focusing on operational excellence and continuous innovation. Successfully stabilized and expanded business operations in new verticals, particularly in the Retail and CPG sectors, driving significant business growth and establishing long-term client relationships.

Senior Manager Data Science at eClerx, Jun 2021 - Jan 2024 · 2 yrs 8 mos, As a strategic leader in the field of data science and analytics, I had the privilege of working with retail and marketing domain giants, leveraging my expertise to drive transformative outcomes. • Collaborated closely with leading retail organizations, establishing strong partnerships and guiding teams in developing machine learning (ML) products tailored to the industry's unique challenges and opportunities. • Successfully implemented ML architectures and Azure Cloud solutions for retail giants, optimizing data analytics capabilities and empowering datadriven decisionmaking processes. • Led a team of professionals, consisting of data scientists, data engineers, and data analysts, in executing projects for retail and marketing domain giants. • Built a collaborative and innovative environment that fostered the exchange of ideas and datadriven decisionmaking, resulting in impactful solutions and improved business outcomes. • Supported the sales team in solutioning and closing deals with major retail and marketing companies, understanding their requirements and aligning our data science and analytics offerings with their business objectives. • Spearheaded the establishment of governance and compliance teams for cloud platforms, ensuring data security and privacy in compliance with industry regulations for retail domain giants. • Demonstrated expertise in working with leading cloud platforms, including Azure, GCP, and AWS, and architecting solutions that drive efficiency, scalability, and costeffectiveness for retail and marketing organizations. • Leveraged the power of Databricks, PySpark, and other advanced tools and technologies to unlock valuable insights from vast amounts of retail and marketing data, enabling improved customer targeting, personalized marketing strategies, and enhanced operational efficiency.

Lead Data Scientist at Serrala, Dec 2020 - Jun 2021 · 7 mos, Pune Division, Maharashtra, India, Cultivated collaborative environments with businesses to establish requirements and develop new Machine Learning (ML) products. Supervise and drive team, overseeing implementation design of ML architecture and ML implementation of Azure Cloud. Managed Anomaly detection of payments at payment message and item level. Classified General Ledger (GL) through payment text and Chatbots using Google Dialog Flow Framework. Designed Voice to speech synthesis using Azure which could take notes in meetings from audio calls, make informed decisions, and assist users in performing actions based on meeting notes ● Utilised Azure Machine Learning and Azure ML SDK to develop ML Projects and led & managed a team of seven members. ● Successfully improved architecture, saving $10-12K annually, and implemented new use cases in ML to generate revenue of about $1M. ● Spearheaded migration of all ML projects to the cloud, redesigning projects to improve accuracy and automate ML pipelines. ● Led a team consisting of five members in completing ML transformation.

Lead Data Scientist at Wipro Limited, Jan 2020 - Dec 2020 · 1 yr, Pune Division, Maharashtra, India, I determined business requirements and developed new ML products. Moreover, I executed tasks in line with assigned timeframe to meet product forecast demands. My role required me to utilise ML frameworks including DataRobot and H2o Driverless AI. I supervised a team of five people and demonstrated proficiency in Azure Machine Learning and Azure ML SDK. Key Accomplishments: • Created 150+ machine learning models and automated complete cycle of data collection, training, testing, and deployment. • Delivered highly efficient architecture to maintain major ML application which predicted future product demands from various segments of Banking and Finance Industry for CITIGROUP.

Education

B.TECH, Hindustan Institute of Technology & Management

INTERMEDIATE, Physics,Chemistry,Mathematics, kendriya vidyalaya