Alex
Bates

Led the design and delivery of enterprise Generative AI solutions using Azure OpenAI, Azure AI Search, AWS Bedrock, and Vertex AI, enabling intelligent document search, conversational AI, and knowledge assistants for financial services clients. Architected large-scale RAG platforms integrating vector databases, semantic search, and hybrid retrieval, significantly improving response accuracy and reducing hallucinations. Built AI orchestration services with Python, FastAPI, and Java, and deployed intelligent AI agents using LangGraph, AutoGen, CrewAI, and MCP integrations.

Developed enterprise Generative AI applications using React, Python, OpenAI, LangChain, Pinecone, MongoDB, and Redis, delivering intelligent search, conversational AI, and knowledge management solutions. Designed RAG pipelines with prompt engineering, embeddings, and vector search to improve answer quality and LLM grounding. Built scalable AI services and REST APIs, and deployed cloud-native solutions on AWS with Docker, Kubernetes, Terraform, and CI/CD.

Delivered enterprise web features that increased user engagement by 25% and achieved 99.99% availability for core workflows in a large-scale production environment. Optimized transactional workflows and tightened CI/CD release gates, reducing response times by 20%. Standardized build and deployment pipelines across teams, cutting build failures by 40%.

Implemented advanced provider search functionality using Angular (TypeScript), ASP.NET Core, and Redis caching, improving data retrieval accuracy and performance. Refactored 36 lookup models to improve data consistency and maintainability. Supported over 5,000 users by enhancing AngularJS, Java, and Python applications, using Maven automation and database optimizations to improve usability and performance.