We're 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 recent 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.

📌 AI Engineer with AWS (India)
🏢 TRIGENT SOFTWARE PRIVATE
📍 India