Architect

Job Requirements

CLOUD AI SERVICES PRACTICE

• AMAZON WEB SERVICES
  
  

Cloud AI Engineer — Agentic AI & Generative AI (AWS)

Experience: 10-15 years

We are looking for a senior engineer with 7—10 years of overall 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