AWS AI Engineer

V Group Inc.; Bengaluru; Hybrid; INR 3,000,000 - 5,500,000; Full time

Benefits offered by this job

Health & Accident Insurance

Paid Leaves and Sick Leaves

Education sponsorship / Certification

Free Training Platforms

Gym membership

EPF, Gratuity

Job summary

V Group Inc. seeks an experienced AWS AI Engineer to design, deploy, and operate production-grade multi-agent AI solutions on AWS Bedrock. You will prototype new AI ideas, implement orchestration and HITL, and deliver secure, scalable production systems across enterprise APIs and data sources.

You will work from established designs, rapidly prototype POCs, and ensure high reliability, performance, and cost efficiency while maintaining strong security controls.

Qualifications

• 5+ years of software engineering or AI/ML engineering experience with strong Python
• Hands-on LangGraph, LangChain and production experience with Agentic AI/multi-agent systems
• Strong AWS experience including Amazon Bedrock and Bedrock AgentCore, plus MCP/A2A implementation
• Solid knowledge of RAG, LLMs, embeddings, vector search, tool calling, state/memory and HITL
• Experience with APIs/FastAPI, Docker, Git, CI/CD, automated testing, AI evaluation, guardrails, observability and production debugging
• Ability to understand established designs and deliver production-grade solutions quickly

Responsibilities

• Build and deploy multi-agent solutions on AWS using Python, LangGraph, and LangChain
• Prototype/POC and productionize successful approaches with secure, scalable outcomes
• Implement orchestration, tool calling, state/memory, checkpointing and HITL; build MCP and A2A capabilities
• Develop RAG/LLM solutions integrated with enterprise APIs and data
• Build and operate on AWS using Amazon Bedrock and Bedrock AgentCore; develop production APIs
• Implement automated testing, CI/CD, AI evaluation, guardrails, observability and security controls
• Troubleshoot and optimize live solutions for reliability, performance, latency and cost

Skills

Python

LangGraph

LangChain

Agentic AI

multi-agent

AWS

Amazon Bedrock

Bedrock AgentCore

MCP

A2A

RAG

LLMs

embeddings

vector search

HITL

API/FastAPI

Docker

Git

CI/CD

guardrails

observability

production debugging

SAP exposure

Tools

Terraform/CloudFormation

Kubernetes/EKS

OpenTelemetry

LangSmith

SageMaker/MLflow

Job description

JD for AWS AI Engineer

Job Details:

• Position Title: AWS AI Engineer
• Job Location: Bangaluru
• Experience: 5+ years

Roles and Responsibilities

Were looking for a hands‑on Senior AI Engineer with a strong software engineering background to build, deploy and operate production-grade Agentic AI and multi-agent solutions on AWS. You’ll work from established designs, freely explore and experiment with new AI ideas, rapidly prototype/POC, and turn successful approaches into secure, scalable production solutions.

This is an engineering and delivery role, not an architecture role.

What You’ll Do

• Build and deploy multi-agent solutions using Python, LangGraph and LangChain; rapidly Prototype/POC and productions successful approaches.
• Implement orchestration, tool calling, state/memory, checkpointing and Human-in-the-Loop (HITL); build and integrate MCP and A2A capabilities.
• Develop RAG/LLM solutions integrated with enterprise APIs, data and business systems.
• Build and operate on AWS using Amazon Bedrock and Amazon Bedrock AgentCore. Develop production APIs and integration services.
• Implement automated testing, CI/CD, AI evaluation, guardrails, observability and security controls including IAM, least privilege, secrets management and secure tool/API access.
• Troubleshoot and optimize live solutions for reliability, performance, latency and cost.

What You’ll Bring

• 5+ years of software engineering, AI/ML engineering or related development experience, with strong Python software engineering skills.
• Strong hands‑on LangGraph/LangChain and proven production experience with Agentic AI and multi‑agent systems.
• Strong hands‑on AWS, Amazon Bedrock and Amazon Bedrock AgentCore, plus MCP and A2A implementation experience.
• Strong knowledge of RAG, LLMs, embeddings, vector search, tool calling, state/memory and HITL.
• Experience with APIs/FastAPI, Docker, Git, CI/CD, automated testing, AI evaluation, guardrails, observability and production debugging.
• Ability to quickly understand established designs and independently deliver production‑quality solutions at pace.

Production Experience – Essential

Must have personally built, deployed and supported at least two production‑grade multi‑agent AI solutions. POC, tutorial, certification or hackathon‑only experience is not sufficient.

Team & Culture

Hands‑on engineering, experimentation, knowledge sharing and continuous learning. You’ll have the freedom to explore new Agentic AI technologies and ideas, share reusable patterns and help shape AI initiatives while maintaining strong security and production engineering standards.

Good to Have

• Broader AWS services
• Terraform/CloudFormation
• Kubernetes/EKS
• OpenTelemetry/LangSmith
• SageMaker/MLflow
• Azure/GCP exposure
• Experience working in SAP environments or integrating AI solutions with SAP is a bonus.

Preferred AI Certifications

• AWS Certified Generative AI Developer – Professiona
• AWS Certified Machine Learning Engineer – Associate
• Hands‑on production experience takes priority over certifications.

Perks & Benefits

• Health & Accident Insurance
• Paid Leaves and Sick Leaves
• Education sponsorship / Certification Reimbursement
• Free Training Platforms
• Gym membership
• EPF, Gratuity.