AWS AI Engineer
NTT Ltd. (company site, opens in a new tab)5+ yrsBengaluruOn-siteDirect career pageEst. 20–35 LPA
Posted 21h ago
Reach people at NTT Ltd.
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at NTT Ltd. you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- Build, deploy and operate production-grade multi-agent AI solutions using Python, LangGraph, LangChain and AWS services including Amazon Bedrock and AgentCore.
- Develop and integrate RAG/LLM solutions with enterprise APIs and business systems, implementing orchestration, tool calling, state/memory management, checkpointing, and Human-in-the-Loop (HITL).
- Ensure solutions are production quality with automated testing, CI/CD pipelines, AI evaluation, security controls (IAM, least privilege, secrets management), and optimize for reliability, performance, latency, and cost.
Minimum Requirements
- 5+ years of software engineering, AI/ML engineering or related development experience with strong Python skills.
- Proven production experience personally building, deploying, and supporting at least two multi-agent AI solutions; POC or tutorial experience inadequate.
- Strong hands-on experience with LangGraph, LangChain, AWS including Amazon Bedrock and Bedrock AgentCore, and implementation of MCP and A2A capabilities.
- Experience with APIs/FastAPI, Docker, Git, CI/CD, automated testing, AI evaluation, guardrails, observability, and production debugging.
Ideal Candidate Profile
- Experienced in rapid prototyping and independently delivering production-quality AI solutions from established designs under pace.
- Comfortable with hands-on implementation and operational responsibilities rather than pure architecture roles.
- Able to maintain strong security and production engineering standards while exploring and experimenting with new Agentic AI technologies and ideas.