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 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 securetool/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.
- Solid 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, uardrails, 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, sharereusable 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 – Professional
- AWS Certified Machine Learning Engineer – Associate
- Hands-on production experience takes priority over certifications.

📌 AI Engineer (Bengaluru)
🏢 Trigent Software - Professional Services
📍 Bengaluru