Deepa A.

AI agents and MCP, large-scale web scraping, and production APIs on AWS, built by an architect with $2M+ earned and 100% Job Success. Most of my clients need three things working together: AI agents that act on their real systems, scraping and data pipelines that feed those systems clean data, and APIs and cloud infrastructure that keep everything running. I build all three. I'm an AWS Certified Solutions Architect with 15+ years building platforms that have to keep working: rate limits, retries, bad inputs, blocked requests, cost per call, and deploys that can't break production. 𝗦𝗢𝗠𝗘 𝗡𝗨𝗠𝗕𝗘𝗥𝗦 ▪ $2M+ earned on Upwork, 100% Job Success, 5.0 from 49 reviews ▪ 60+ enterprise projects, 28,000+ hours ▪ Multi-year clients: one data platform from 2022 to 2026, a back-end engagement for 2.5+ years ▪ "Deepa is one of the best programmers I know." (client review) 𝗔𝗜 𝗔𝗚𝗘𝗡𝗧𝗦 𝗔𝗡𝗗 𝗠𝗖𝗣 ▪ Custom Python MCP servers that let Claude, ChatGPT or your agents securely use your databases, APIs, Microsoft 365 email, SharePoint, Confluence, Google Docs, HubSpot and Slack ▪ Multi-agent LangGraph workflows with tool routing, persistent memory and human escalation, plus RAG on Pinecone, pgvector or Qdrant with access controls ▪ Workflow automation, OCR on images and TIFFs, document extraction and computer vision; fine-tuning with Amazon Bedrock and SageMaker HyperPod 𝗪𝗘𝗕 𝗦𝗖𝗥𝗔𝗣𝗜𝗡𝗚, 𝗗𝗔𝗧𝗔 𝗔𝗡𝗗 𝗚𝗘𝗢𝗦𝗣𝗔𝗧𝗜𝗔𝗟 ▪ High-volume scraping of heavily protected sites such as Amazon, Walmart, Home Depot and Wayfair, with robust CAPTCHA and anti-bot handling ▪ Playwright, Selenium, Scrapy and Puppeteer, distributed with Celery and rotating proxies (Bright Data) ▪ Near-real-time scraping of natural gas pipeline flows to model supply and demand curves ▪ For a Florida attorney: identified foreclosure homes across Florida county records databases and decoded specific legal details from scanned records with OCR ▪ Pipelines that clean, normalize, deduplicate and link scraped data to your master dataset. SEC EDGAR financial statements and holdings ▪ ETL/ELT on Airflow, Kafka, dbt and Spark into Snowflake, BigQuery, Redshift, Databricks and PostgreSQL ▪ Geospatial: GDAL and GeoPandas, high-resolution satellite tasking with the Planet API, and detection and prediction models validated on large AIS vessel-track, imagery and time-series datasets 𝗔𝗣𝗜𝗦, 𝗖𝗟𝗢𝗨𝗗 𝗔𝗡𝗗 𝗖𝗜/𝗖𝗗 ▪ API development in Python and FastAPI: REST, webhooks, OAuth2, JWT, RBAC and SSO ▪ Third-party integrations: HubSpot, Slack, social media, Shopify Admin and Storefront, credit card payments, flight search and booking ▪ AWS deployments on ECS and Fargate, Lambda, API Gateway, S3, DynamoDB and OpenSearch, plus Azure and GCP, designed for 99.9% uptime ▪ CI/CD pipelines with GitHub Actions and Jenkins, infrastructure as code with Terraform, Docker and Kubernetes, zero-downtime releases across AWS, Azure and GCP ▪ Monitoring and observability (Prometheus, Grafana), performance optimization, legacy code conversion and migration 𝗔𝗟𝗦𝗢 𝗘𝗫𝗣𝗘𝗥𝗜𝗘𝗡𝗖𝗘𝗗 𝗜𝗡 ▪ Ecommerce: Shopify inventory, orders and shipping, selling a Shopify catalog on a non-Shopify site, Liquid, Klaviyo, Amazon FBA ▪ Analytics & BI: dashboards in Looker, GA4 and Tag Manager; SPSS, Stata and SAS ▪ Power Platform, Dynamics 365, Salesforce, Entra ID, Python and shell automation, AI data labeling 𝗥𝗘𝗖𝗘𝗡𝗧 𝗪𝗢𝗥𝗞 An MCP-enabled options analytics platform with real-time market flow, Greeks and gamma exposure. Retail scraping pipelines for Walmart, Kroger and Target. Enterprise Q&A assistants with persistent memory. AI legal-case monitoring. Case studies are in my portfolio. 𝗦𝗧𝗔𝗖𝗞 Claude, MCP, OpenAI, LangGraph, LangChain, Bedrock, Python, FastAPI, Playwright, Scrapy, Selenium, Celery, GeoPandas, GDAL, Airflow, Kafka, Snowflake, PostgreSQL, Redis, AWS (ECS, Lambda, API Gateway, S3), Azure, GCP, Docker, Kubernetes, Terraform, GitHub Actions, Jenkins 𝗦𝗧𝗔𝗥𝗧 𝗛𝗘𝗥𝗘 Tell me what you need to built, scraped or deployed, and which systems it touches. I'll reply within the day with how I'd approach it.