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SageMaker","optional":true},{"name":"Azure","optional":true},{"name":"CloudFormation","optional":true},{"name":"GCP","optional":true},{"name":"Kubernetes","optional":true},{"name":"LangSmith","optional":true},{"name":"Machine Learning","optional":true},{"name":"MLFlow","optional":true},{"name":"OpenTelemetry","optional":true},{"name":"Terraform","optional":true}],"status":"live","first_seen_at":"2026-10-11T17:46:29Z","employer_posted_date":null,"last_verified_at":"2026-10-11T17:46:29Z","board_verified":false,"closed_at":null,"days_open":2,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":2},"description":"Hiring: Senior AWS AI Engineer – Agentic AI / Multi-Agent Systems\nLocation: Bangalore / Gurgaon / NCR\nExperience: 6+ Years\nWork Mode: As per project/client requirement\nWe are 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.\nThis 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experience with LangGraph & LangChain\n Production experience with Agentic AI & Multi-Agent Systems\n Hands-on experience with AWS, Amazon Bedrock & Bedrock AgentCore\n Experience with MCP & A2A\n Strong knowledge of RAG, LLMs, embeddings, vector search, tool calling, state/memory & HITL\n Experience with APIs/FastAPI, Docker, Git & CI/CD\n Experience with AI evaluation, guardrails, observability and production debugging\n Production Experience – Mandatory\nCandidates must have personally built, deployed and supported at least 2 production-grade Multi-Agent AI solutions.\n POC-only, tutorial, certification or hackathon experience will not be considered sufficient.\n Good to Have\n• Terraform / CloudFormation\n• Kubernetes / EKS\n• OpenTelemetry / LangSmith\n• SageMaker / MLflow\n• Azure / GCP exposure\n• SAP integration / SAP environment experience\n Preferred Certifications\n• AWS Certified Generative AI Developer – Professional\n• AWS Certified Machine Learning Engineer – 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