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Senior GenAI Engineer with an MS in Computer Science from the University of Illinois Chicago and three AWS certifications: Developer - Associate, AI Practitioner, and Cloud Practitioner. I build production AI agents, chatbots, voice agents, RAG systems, and workflow automation on AWS: systems that use tools, access business data, maintain state, and complete multi-step workflows reliably. Currently open for new client projects. Why Work With Me - I build the full product around the model, not just the model call: agent orchestration, backend APIs, frontends, databases, authentication, state and memory, deployment, and failure handling. - Model-agnostic by design: Claude, OpenAI GPT, or Amazon Nova (Nova 2 Sonic for real-time voice), whichever clears your quality bar at the lowest cost and latency, on pay-per-use serverless with typical p95 of 0.7 to 2.0 seconds per turn. - Agents that know when to stop: explicit confirmations before consequential actions, and clean human handoff when automation should end. Project Highlights Agent-Builder Platform: Chat + Voice Agents (in-house, 2026) - Led design and development of an AWS-native platform where customers turn complex, form-driven business workflows into AI agents and deploy them to their websites - Chat agents guide users through workflows, clarify questions, maintain conversational and form state, and collect structured data instead of static forms - Low-latency voice agents (Amazon Nova 2 Sonic) complete the same workflows through real-time conversation with the same tools and knowledge - Agent execution layer integrates knowledge bases, MCP tools, document verification, conditional logic, multilingual support, and external APIs - Built end to end (frontend, backend, agent orchestration, state management, serverless AWS) with reusable components so new workflows are configured rather than re-engineered AI Fraud Analyst: natural-language investigations over Redshift - Multi-agent Bedrock assistant (MCP to Redshift) that turns plain-English questions into controlled, schema-aware SQL and returns an evidence-backed brief with a 0-10 fraud-likeness score - Deterministic plan → query → validate → run → summarize loop; handles multi-table joins, including 4-table joins across a ~6-7 table surface - Safety-first execution: read-only access, allowlisted schemas, parameterized queries, preflight checks, and full query/tool-call traceability - Stack: AWS Bedrock, MCP server, Redshift Serverless, IAM, CloudWatch Policy Bot: personalized benefits discovery (hierarchy-aware RAG) - Takes a person's circumstances (a low-income student, a single parent, a widower) and surfaces the federal, state, and local policies that benefit them - Resolves precedence between federal, state, and local rules and weighs policy recency, so newer, higher-authority policies override outdated ones E-commerce AI Automation: gift-card issuance over web and email - Verifies orders in real time via the Amazon Orders API, issues gift cards through the Amazon Incentives API, updates records, and sends branded emails - Extended into a session-aware email agent (SES → S3 → Lambda → Bedrock) preserving context across threads, so teams can work from their inbox - Measured conversation cost of 0.01 to 0.03 USD on Claude Haiku, saving teams 2 to 5 minutes per request - Stack: AWS Bedrock, AgentCore, API Gateway, Lambda (TypeScript), DynamoDB, SES, S3, CloudWatch WhatsApp B2B Ordering Agent - WhatsApp-native ordering assistant handling cart updates, order confirmations, and reliable human handoff - Transactional flow with explicit confirmations before every action to reduce unintended orders - Stack: Fastify, Amazon Bedrock, WhatsApp Business API, Redis, PostgreSQL Security by Default - Platform security from the start: least-privilege IAM, auth boundaries, secrets management, encryption, VPC isolation, audit logging, environment separation, and GDPR- and SOC 2-aware design - Agentic security on top: tool permissions, data-access boundaries, input validation, controlled side effects, idempotency, and traceability. An LLM with real tools and business data has failure modes that ordinary chatbots do not How I Work - A working demo comes first, then we iterate on the real thing - Weekly shippable phases, daily async communication, and transparent reporting of speed, cost, and quality: dashboards, not mysteries Bring me the workflow you want automated end to end. I'll come back with a plan, a latency target, and a cost-per-conversation estimate. Core technologies: Generative AI, Agentic AI, AI Agents, AI Chatbots, Voice AI, Voice Agents, ChatGPT, Claude, Amazon Nova, Nova 2 Sonic, Amazon Bedrock, Bedrock Agents, AgentCore, MCP, RAG, Amazon Q, Amazon Lex, AWS Lambda, API Gateway, DynamoDB, S3, SES, IAM, Cognito, CloudWatch, Redshift, PostgreSQL, Redis, Python, TypeScript, Node.js, React, Next.js, Fastify, REST APIs, LangChain, LangGraph, Terraform, Docker.

I'm a Senior Data Engineer with 4.5+ years of experience building scalable, cloud-native data platforms that turn raw data into reliable, business-ready insights. I've delivered enterprise solutions across banking (NAB), healthcare (Molina), and CPG (PepsiCo), specializing in end-to-end pipeline architecture, data modeling, and cloud migrations. What I bring to your project: 🔹 Cloud Data Engineering – Deep expertise in Azure (Databricks, Data Factory, Synapse) and AWS (EMR, Glue, S3, RedShift), with hands-on migration experience from on-prem and Teradata to cloud. 🔹 Pipeline Architecture & ETL – I design and build robust ingestion frameworks handling batch, incremental, and real-time data (Event Hub, Kafka) across formats like JSON, CSV, Parquet, and fixed-width files. 🔹 Data Modeling & Warehousing – Skilled in dimensional modeling, Data Vault, star/snowflake schemas, and silver/gold layer design. I've modeled 50+ tables across Oracle Fusion, SAP S/4, and healthcare domains. 🔹 Transformation & Orchestration – I translate complex business rules into DBT models, orchestrate workflows with Apache Airflow or AutoSys, and automate CI/CD via Jenkins and Azure DevOps. 🔹 Performance & Governance – I tune PostgreSQL and Spark jobs, implement data quality checks, reconciliation frameworks, and ensure compliance with data governance standards. 🔹 Generative AI & MLOps – Databricks-certified in Generative AI, with experience integrating MLflow for experiment tracking and building LLM-based automation using OpenAI and LangChain. Tech Stack: Python | SQL | Scala | Apache Spark | DBT | PostgreSQL | Snowflake | Airflow | Databricks | Azure | AWS | Git | Jenkins | MLflow | Power BI Certifications: Databricks Certified Data Engineer Professional | Azure Data Engineer (DP-203) | Snowflake SnowPro Core | Fabric Analytics Engineer (DP-600) | Generative AI Engineer Associate Whether you need a production-grade pipeline, a cloud migration, or a well-modeled data warehouse, I deliver clean, documented, and scalable solutions — on time and with clear communication. Let's discuss your project!

I help post-Series-A and enterprise teams turn messy data into the dashboards their executives actually open, and increasingly, the AI agents that act on what those dashboards show. 12 years in BI and data engineering. Top Rated Plus on Upwork for a decade. 200+ clients, 12,000+ hours billed, $300K+ earned here. Where I've worked at depth: - Google (Chronicle / Siemplify) - built their entire BI infrastructure as their first BI hire; stayed five years through the Google acquisition. - British American Tobacco (MAF Group) - Head of Data; built a team of 15 and 100+ pipelines. - Boston Consulting Group - Lead Tableau + Dataiku mentor for 20+ analysts. - Teambuilder (Google Startups) - Tableau→Looker multi-tenant architecture, still active. Three things I do better than most: - BI architecture, not just dashboards. Tableau Certified Architect (2025), Google Certified Professional Data Engineer. I design the warehouse + semantic layer + governance, not just the front-end chart. - Migrations without business downtime. Power BI ↔ Tableau, Cognos → Power BI, Tableau → Metabase/Superset, GA/Adobe → BigQuery. I've done the messy ones. - AI layered on top of BI. Currently building Claude/MCP-driven workflows for proposal analysis, dashboard QA, and decision-agent prototypes. Enrolled in IIT Kharagpur's GenAI + Agentic AI programme (May 2026 – Jan 2027). ⭐⭐⭐⭐⭐ 5.00 across 80+ Jobs 🥇𝗢𝗳𝗳𝗶𝗰𝗶𝗮𝗹 𝗧𝗮𝗯𝗹𝗲𝗮𝘂 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗲𝗱 𝗗𝗲𝘀𝗸𝘁𝗼𝗽 𝗦𝗽𝗲𝗰𝗶𝗮𝗹𝗶𝘀𝘁 𝗮𝗻𝗱 𝗦𝗲𝗿𝘃𝗲𝗿 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁 🥇𝗢𝗳𝗳𝗶𝗰𝗶𝗮𝗹 𝗚𝗼𝗼𝗴𝗹𝗲 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗲𝗱 𝗟𝗼𝗼𝗸𝗲𝗿 / 𝗟𝗼𝗼𝗸𝗠𝗟 𝗗𝗲𝘃 🏆Top Rated Plus for 10 Years, 200+ clients, 12000+ hours worked 🏢𝗘𝗺𝗶𝗻𝗲𝗻𝘁 𝗖𝗹𝗶𝗲𝗻𝘁𝘀 𝗜 𝗵𝗮𝘃𝗲 𝘄𝗼𝗿𝗸𝗲𝗱 𝘄𝗶𝘁𝗵 (𝗝𝘂𝘀𝘁 𝘁𝗵𝗲 𝗯𝗲𝘀𝘁 𝗼𝗳 𝘁𝗵𝗲𝗺) » Google (Google Chronicle) » Boston Consulting Group (BCG) » British American Tobacco » Teambuilder » Hamptons (Emaar) 💡 𝗥𝗲𝗮𝗹 𝗯𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝗽𝗿𝗼𝗯𝗹𝗲𝗺𝘀 𝗜 𝗵𝗮𝘃𝗲 𝘀𝗼𝗹𝘃𝗲𝗱 » Digital Marketing Dashboards integrating Google Ads, Facebook Ads, Reddit Ads data » Tracking Cost, LTV, CLTV, ROAS, CAC, RoI for Digital Marketing Agencies and Companies » eCommerce BI pipelines and dashboards integrating data from Shopify, Magento, Amazon API and various other eCommerce sources » Web Analytics dashboards integrating Google Analytics, Adobe Analytics and Posthog 💡4 𝗥𝗲𝗮𝘀𝗼𝗻 𝘄𝗵𝘆 𝘆𝗼𝘂 𝘄𝗶𝗹𝗹 𝗻𝗼𝘁 𝗿𝗲𝗴𝗿𝗲𝘁 𝗰𝗵𝗼𝗼𝘀𝗶𝗻𝗴 𝗺𝗲 ✔️ 99% Client Success Ratio. My clients particularly love me because I stick through particularly during the hard days ✔️ All Round expertise - Experience with wide variety of tools in Data Visualization, Data Engineering, Data Governance and Gen AI prepares me for complex all-rounder expertise ✔️ 2 years - Average Client Retention time period since I started in Upwork ✔️ Communication & Business Knowledge - I understand what the client wants even though it's a small technical work. And so I deliver what they want and what they need 🛠️𝗠𝘆 𝗧𝗲𝗰𝗵 𝗦𝘁𝗮𝗰𝗸 𝘿𝙖𝙩𝙖 𝙑𝙞𝙨𝙪𝙖𝙡𝙞𝙯𝙖𝙩𝙞𝙤𝙣 𝙏𝙤𝙤𝙡𝙨 ✔️ Tableau Desktop ✔️ Tableau Server ✔️ Looker ✔️ LookML ✔️ Looker Studio ✔️ Metabase ✔️ Qlik ✔️ Domo 𝘿𝙖𝙩𝙖 𝙀𝙣𝙜𝙞𝙣𝙚𝙚𝙧 / 𝘿𝙖𝙩𝙖 𝙒𝙖𝙧𝙚𝙝𝙤𝙪𝙨𝙚 ✔️ Google Bigquery (Google Certified Professional Data Engineer) ✔️ Snowflake ✔️ Postgres ✔️ Azure Data Lakehouse ✔️ Microsoft SQL Server ✔️ Amazon Redshift ✔️ MongoDB ✔️ Python 𝘿𝙖𝙩𝙖 𝙎𝙤𝙪𝙧𝙘𝙚𝙨 (𝘼𝙘𝙦𝙪𝙞𝙨𝙞𝙩𝙞𝙤𝙣) ✔️ Google Analytics (UA, GA4) ✔️ Adobe Analytics ✔️ Shopify ✔️ Magento ✔️ Amazon eCommerce ✔️ Qualtrics ✔️ IMS Claims ✔️ Google Ads ✔️ Facebook & Instagram Ads ✔️ Reddit Ads ✔️ Salesforce CRM ✔️ Pipedrive CRM ✔️ Go High Level CRM 𝗖𝘂𝘀𝘁𝗼𝗺 𝗦𝗲𝗿𝘃𝗶𝗰𝗲𝘀 𝗜 𝗼𝗳𝗳𝗲𝗿 ✔️ Tableau Desktop Report Creation ✔️ Tableau Server Administration ✔️ Tableau Server Installation ✔️ Tableau Server Upgrade ✔️ Tableau Server backup automation ✔️ Tableau Server Automated Metadata extraction ✔️ Power BI to Tableau Migration ✔️ Excel or Google Sheets to Tableau Migration ✔️ Tableau Prep Flow creation ✔️ Tableau Pulse ✔️ Tableau to Power BI Migration ✔️ IBM Cognos to Power BI Migration ✔️ Tableau to Metabase Migration ✔️ Tableau to Apache Superset Migration ✔️ Tableau Rest API ✔️ LookML Data Modeling and Semantic Layer Development ✔️ Looker Implementation, Setup, and Data Source Integration ✔️ Embedded Analytics and Looker API Integration ✔️ Looker Performance Optimization and Health Checks ✔️ LookML Git Setup ✔️ Rapid Metabase Deployment & Setup ✔️ Metabase User Enablement & Self-Service Training ✔️ Metabase/SQL Optimization & Caching ✔️ Data Modeling & Metadata Governance

🏆 AWS Certified Generative AI Developer - Professional 🏆 AWS Certified Machine Learning – Specialty 🏆 AWS Certified Data Analytics – Specialty 🏆 Google Cloud Professional Machine Learning Engineer 🏆 Google Cloud Professional Cloud Architect I help businesses design, build, and deploy production-ready Generative AI applications powered by LLMs, AI Agents, RAG pipelines, Voice AI, and workflow automation. With 8+ years of experience in Machine Learning, NLP, Computer Vision, and Cloud AI, I specialize in transforming AI prototypes into scalable, enterprise-grade solutions running on AWS, GCP, and Kubernetes. What I Build ✅ AI Agents & Agentic Workflows * Single-Agent & Multi-Agent Systems * LangGraph Agent Development * MCP (Model Context Protocol) Integrations * Tool Calling & Function Calling Agents * Autonomous Research & Task Execution Agents * AI Workflow Automation ✅ RAG & Enterprise Search * Retrieval-Augmented Generation (RAG) * Enterprise Knowledge Assistants * Internal Documentation Chatbots * PDF, SharePoint, Confluence & Website Search * Hybrid Search (Vector + Keyword) * Agentic RAG Architectures ✅ Conversational AI & Voice AI * AI Chatbots * Customer Support Assistants * AI Voice Agents * Call Center Automation * Real-Time Speech-to-Speech Applications * Voice Ordering & Appointment Booking Systems GenAI Technologies 📍 LLMs OpenAI GPT-4o, GPT-5, Claude, Gemini, Llama, Mistral, Gemma, AWS Bedrock 📍 Agent Frameworks LangGraph, LangChain, LlamaIndex, CrewAI, AutoGen, LangSmith, LangFuse 📍 Vector Databases Pinecone, Qdrant, Weaviate, Milvus, ChromaDB, pgvector, Elasticsearch, Redis 📍 Voice AI Vapi, ElevenLabs, Deepgram, AssemblyAI, Whisper 📍 Prompt Engineering & Optimization DSPy, TextGrad, Structured Outputs, Guardrails 📍 LLM Deployment vLLM, Hugging Face TGI, TensorRT-LLM, Ray Serve, TorchServe Machine Learning & MLOps 📍 TensorFlow 📍 PyTorch 📍 Hugging Face 📍 Scikit-Learn 📍 Spark ML 📍 Forecasting & Predictive Analytics 📍 Computer Vision Solutions Cloud & Infrastructure AWS: Bedrock, SageMaker, Lambda, ECS, EKS, Textract, Comprehend, Rekognition, Transcribe, Polly, Forecast, Personalize Google Cloud: Vertex AI, Agent Builder, Gemini, Document AI, Dialogflow CX, GKE, Cloud Run, Cloud Functions Azure: Azure OpenAI, Azure ML Infrastructure: Kubernetes, Docker, CI/CD, GitHub Actions, Terraform Industries Served ✔ Retail & eCommerce ✔ Manufacturing ✔ Supply Chain & Logistics ✔ Automotive ✔ Healthcare ✔ Financial Services ✔ Customer Support Operations Whether you need an AI Agent, RAG chatbot, Voice AI solution, LLM-powered application, or a complete GenAI platform deployed on AWS/GCP, I can help take your idea from concept to production.