Shaik Fayeemuddin

AI Engineer with 3 years of experience, including enterprise-grade Generative AI systems in Banking and Life Science domains. Specialized in Agentic AI platforms, Retrieval-Augmented Generation (RAG) systems, Multi-model LLM gateways (OpenAI + AWS Bedrock), Guardrails and enterprise AI governance, and Production deployment on AWS. Proven experience designing and deploying AI solutions for Bristol Myers Squibb (BMS) and Citizens Bank (US).

Strong architectural mindset with hands-on expertise in FastAPI, AWS, Bedrock, embeddings, and observability-driven AI systems.

AI Engineer – Enterprise Agentic AI platform - Cognizant Technology solutions

(2023-01)

Citizens Bank, a prominent U.S. banking institution, established its Global Capability Centre (GCC) in Hyderabad in collaboration with Cognizant to drive innovation and technology transformation across its Banking and Financial Services operations.

• Designed and built an enterprise-grade Agentic AI platform enabling secure tool-calling, multi-model orchestration, and controlled AI workflows tailored for banking use cases.
• Architected a custom LLM Gateway integrating both OpenAI and AWS Bedrock models, supporting dynamic model routing, extensibility, and centralized governance.
• Implemented advanced agentic workflows using AWS Strands framework, supporting multi-step reasoning, conditional execution, and structured tool interaction.
• Deployed agents into AgentCore runtime using Amazon Bedrock AgentCore, ensuring scalable execution and seamless integration with enterprise workflows.
• Designed and developed tool-calling and function-calling architecture, enabling intelligent workflow automation across internal banking services.
• Enabled agent-to-agent communication with conversational memory handling for contextual continuity and state management.
• Implemented custom guardrails for both input text and output response handling, these guardrails internally uses bedrock guardrails.
• Implemented comprehensive observability and logging mechanisms using Splunk and database logging to capture end-to-end agent execution, model interactions, and workflow events.
• Built scalable FastAPI applications to support Splunk logging pipelines and experimental data capture for monitoring.
• Developed use case validation mechanisms to ensure only authorized and approved banking use cases are executed within the platform.
• Implemented an enterprise-level Kill-switch mechanism that can be used to block specific users, use cases, or model IDs, ensuring governance, risk control, and operational safety.

AI Engineer & Power BI Developer - Cognizant Technology solutions

(2023-01)

Bristol Myers Squibb - BMS

• Initially worked as a Power BI Developer, designing and developing interactive dashboards for BMS Real Estate operations to analyze workspace utilization across global properties.
• Built data-driven insights enabling leadership to identify underutilized office spaces, supporting cost optimization and strategic workspace reduction initiatives.
• Designed and implemented a Retrieval-Augmented Generation (RAG) based knowledge assistant for internal managers to access company-specific documentation efficiently.
• Integrated AWS Bedrock APIs to connect with foundation models and embeddings for semantic search and contextual response generation.
• Developed document ingestion, chunking, and retrieval pipelines to enable accurate knowledge extraction from large internal document repositories.
• Significantly reduced manual effort and time spent by management in retrieving company-specific information, improving operational efficiency and decision-making speed.

M.Sc. - Applied Statistics - University college of science, Osmania University (2020-01 - 2022-01)

B.Sc. - Statistics - AV college of Arts Science and Commerce (2017-01 - 2020-01)