Senior AWS Agentic AI Engineer

About the role

The ideal candidate will design, develop, and deploy production-ready AI agents, multi-agent systems, and enterprise AI platforms on AWS using Amazon Bedrock, AWS AgentCore, SageMaker, and cloud-native services.

Responsibilities

• Design and develop Agentic AI solutions supporting reasoning, planning, memory, tool usage, and autonomous task execution.
• Build and deploy Generative AI and LLM-based applications using Amazon Bedrock, AWS AgentCore, SageMaker, and foundation models.
• Develop RAG (Retrieval-Augmented Generation) solutions integrating enterprise knowledge sources, vector databases, and hybrid search.
• Design and implement multi-agent orchestration using LangGraph, LangChain, CrewAI, Bedrock Agents, AWS AgentCore, or similar frameworks.
• Build secure, scalable, and highly available AI platforms using AWS serverless and event-driven services including Lambda, API Gateway, Step Functions, EventBridge, and DynamoDB.
• Integrate AI agents with enterprise applications, APIs, databases, MCP servers, and third-party services.
• Implement AI platform engineering, MLOps, CI/CD, model deployment, evaluation, observability, governance, and lifecycle management.
• Optimize AI applications for performance, accuracy, latency, scalability, reliability, and operational cost.
• Implement Responsible AI, security guardrails, prompt protection, governance, compliance, and monitoring for enterprise AI workloads.
• Collaborate with business stakeholders, solution architects, data engineers, and application teams to deliver innovative AI solutions.
• Provide technical leadership, architecture guidance, and mentoring across engineering teams.

Qualifications

• Experience: 8+ years in AWS Cloud Engineering/Solution Architecture and 3+ years building Agentic AI or Generative AI solutions.
• AWS Services: Amazon Bedrock, AWS AgentCore, SageMaker, Lambda, API Gateway, Step Functions, EventBridge, S3, DynamoDB, OpenSearch, ECS/EKS, IAM, CloudWatch.
• AI Technologies: Agentic AI, LLMs, Multi-Agent Systems, RAG, Prompt Engineering, Vector Databases, AI Evaluation, AI Observability, AI Governance, Responsible AI.
• Frameworks: LangChain, LangGraph, CrewAI, LlamaIndex, Bedrock Agents, AutoGen, MCP (Model Context Protocol).
• Programming: Strong Python development experience; Java, JavaScript/TypeScript, and SQL are a plus.
• DevOps/MLOps: Terraform, CloudFormation, GitHub Actions, Jenkins, Docker, Kubernetes.