Deepa A.

$2M+ earned on Upwork • 100% Job Success • 60+ enterprise projects • 15+ years I architect and build production AI platforms—from MCP and LangGraph agents to RAG, enterprise integrations, data pipelines, backend APIs, and cloud deployment. I help organizations move from AI experimentation to secure, reliable systems that deliver measurable business value. My core strength is enterprise LLM orchestration across Anthropic Claude, OpenAI, Google Gemini, and Amazon Bedrock, backed by deep Python engineering, data platforms, and AWS-certified cloud architecture. 🚀 AI Agents, MCP & RAG Architecture • MCP & Enterprise Tool Integration: Build custom MCP servers and clients in Python, securely connecting AI agents to databases, codebases, documents, private APIs, email, calendars, Slack, CRM, and internal systems. • Agent Orchestration: Design stateful multi-agent workflows with LangGraph, including planning, sub-agent delegation, tool routing, human approval, fallback paths, and context isolation for complex tasks. • RAG & Vector Search: Build retrieval pipelines using Pinecone, pgvector, Qdrant, Weaviate, and OpenSearch for semantic search, enterprise knowledge retrieval, grounded responses, and scalable document intelligence. • Persistent Memory: Implement episodic and semantic memory using conversation logging, fact extraction, vector recall, and relevance-based retrieval so assistants retain useful context across sessions. • Claude Code & Agent Skills: Integrate Claude Code into development workflows and author reusable SKILL.md packages for context-aware engineering automation. • Multi-LLM Architecture: Orchestrate Claude, OpenAI, Gemini, and Bedrock models through LangChain and LangGraph, selecting models based on reasoning quality, latency, reliability, and cost. Recent builds include enterprise Q&A assistants and modular AI systems with pluggable tools and persistent memory, alongside a standout project: an MCP-enabled options analytics platform delivering real-time market flow, Greeks, volatility, and gamma exposure analysis. (Full case studies for legal-case monitoring and real-estate communication systems are in my portfolio.) 📊 Data Engineering & Web Data Acquisition • Resilient Data Acquisition: Build distributed extraction platforms for complex retail, marketplace, API, and client-authorized authenticated environments using Playwright, Selenium, Scrapy, Puppeteer, session management, proxy orchestration, adaptive retries, rate controls, and continuous monitoring. • ETL & Real-Time Data Services: Transform high-volume raw data into validated, structured, queryable datasets and expose them through secure APIs, event streams, and downstream applications. • Pipeline Orchestration: Design scheduled and event-driven pipelines using Airflow, Dagster, Celery, and Kafka, with dependency management, retries, replay, and failure recovery. • Modern Data Platforms: Snowflake, BigQuery, Redshift, Databricks, PostgreSQL, MongoDB, DynamoDB, Redis, and cloud object storage. • Data Governance: Implement OpenLineage and Marquez across pipeline and Celery jobs for traceability, impact analysis, auditability, and operational governance. ⚙️ System Design, Cloud Architecture & Backend DevOps • Solution & System Design: Translate business requirements into technical specifications, architecture diagrams, service boundaries, REST APIs, microservices, event-driven pipelines, and delivery roadmaps. • AWS Architecture: Design secure, fault-tolerant platforms for availability targets up to 99.9% using S3, Lambda, DynamoDB, API Gateway, OpenSearch, container services, private networking, and managed data services. • Multi-Cloud Delivery: Architect solutions on Azure using Azure Functions, Azure DevOps, and Cosmos DB, and on Google Cloud using Cloud Functions, Cloud Run, and BigQuery. • Backend Platforms: Build secure Python and FastAPI services with PostgreSQL, MongoDB, DynamoDB, Redis, Kafka, OAuth2, JWT, RBAC, and SSO. • MLOps & Observability: Use MLflow for experiment and model tracking, with Prometheus and Grafana for service, infrastructure, and pipeline monitoring. • DevOps & Automation: Docker and Kubernetes across AWS, Azure, and GCP; Terraform, Jenkins, and GitHub Actions supporting automated, blue/green, canary, and rollback-ready deployments. 💼 Why Work With Me? I combine hands-on engineering with senior architectural judgment. Clients get clear communication, rigorous documentation, practical technology decisions, and transparent milestones that keep scope, schedule. My Skills: Python, Artificial Intelligence (AI), ChatGPT, OpenAI API, LangChain, Model Context Protocol (MCP), Anthropic Claude, Google Gemini API, AI Agent Architecture, AWS Cloud Architecture, FastAPI, Retrieval-Augmented Generation (RAG), Data Engineering, Web Scraping, Automation, AI Chatbot Development, AI Assistant Development, Amazon Bedrock, DevOps, Docker, Terraform and Kubernetes.