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 environment
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