Job Requirements

CLOUD AI SERVICES PRACTICE

- AMAZON WEB SERVICES

Cloud AI Engineer — Agentic AI & Generative AI (AWS) Experience: 10-15+ years Software/ML engineering experience, including at least 3 years building Agentic AI and Generative AI solutions on AWS, to design, build, and deploy production-grade agentic and GenAI systems across the full AI stack.

Responsibilities

- Architect and build GenAI solutions using Amazon Bedrock and SageMaker AI, selecting and tuning foundation models (Claude, Nova, Llama)
- Design and own Retrieval-Augmented Generation (RAG) pipelines using Titan/Cohere embeddings, Amazon OpenSearch, and Bedrock Knowledge Bases
- Lead development of production AI agents using the Strands Agents SDK, deployed on Bedrock AgentCore (Runtime, Memory, Gateway, Identity)
- Define and enforce responsible-AI guardrails and lead model/agent evaluation before production release
- Own MLOps automation with SageMaker Pipelines and drive fine-tuning/customization of foundation models




- Mentor engineers and guide architecture decisions for agentic AI adoption across teams

Required Skills

- 10-15+ years overall software/ML engineering experience, including at least 3 years hands-on with Agentic AI and Generative AI specifically
- Deep hands-on experience with Amazon Bedrock and/or SageMaker AI in a production setting
- Strong grasp of embeddings, vector search, and Retrieval-Augmented Generation (RAG) architecture
- Practical experience building AI agents with tool-calling via the Model Context Protocol (MCP) and multi-agent coordination via the Agent2Agent (A2A) protocol
- Strong Python and AWS fundamentals (S3, IAM, Lambda, API Gateway)

Preferred

- AWS Certified AI Practitioner or Machine Learning Engineer - Associate
- Experience with MLOps, CI/CD, and production model monitoring at scale

Work Experience 10-15Years

📌 AI Architect (Chennai)
🏢 Virtusa
📍 Chennai