AI Architect

Virtusa; Chennai District; On-site; INR 3,500,000 - 7,000,000; Full time

Job summary

Virtusa in Chennai, India is seeking a senior Cloud AI Engineer to design, build, and deploy production‑grade agentic and GenAI systems on AWS. You will architect GenAI solutions, lead RAG pipelines, and guide model evaluation and guardrails across teams.

The role requires 10–15 years of software/ML experience with at least 3 years in agentic and generative AI on AWS. Hands-on AWS Bedrock/SageMaker and strong Python skills are essential for success.

Qualifications

• 10-15 years overall software/ML engineering experience.
• At least 3 years hands-on with Agentic AI and Generative AI on AWS.
• Deep hands-on experience with Bedrock and/or SageMaker in production.
• Strong grasp of embeddings, vector search and RAG architecture.
• Proficient in Python and AWS fundamentals (S3, IAM, Lambda, API Gateway).

Responsibilities

• Architect and build GenAI solutions using Amazon Bedrock and SageMaker AI.
• Design and own Retrieval-Augmented Generation (RAG) pipelines using embeddings and OpenSearch.
• Lead development of production AI agents using Strands SDK deployed on Bedrock AgentCore.
• Define and enforce responsible-AI guardrails and evaluate models/agents before prod release.
• Own MLOps automation with SageMaker Pipelines and fine-tune foundation models.
• Mentor engineers and guide architecture decisions for agentic AI adoption.

Skills

Agentic AI & GenAI

Amazon Bedrock

SageMaker AI

Embeddings & Vector search

RAG architecture

Python

AWS fundamentals (S3, IAM, Lambda, API

Gateway)

Multi-agent coordination (A2A)

Tools

Amazon Bedrock

SageMaker AI

OpenSearch

Bedrock AgentCore

MCP (Model Context Protocol)

A2A protocol

Python

AWS S3/IAM/Lambda/API Gateway

Job description

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.

CLOUD AI SERVICES PRACTICE

• AMAZON WEB SERVICES

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