AWS Agentic AI Services
Job Summary
We are seeking an experienced AWS Agentic AI Services Consultant with 5+ years of professional experience in cloud-native application development, AI/ML solutions, and AWS services. The ideal candidate will design, develop, and deploy Agentic AI solutions leveraging AWS AI/ML and Generative AI services, enabling autonomous workflows, intelligent agents, multi-agent orchestration, and enterprise-scale AI automation.
This role requires hands-on expertise in AWS cloud services, Generative AI frameworks, Large Language Models (LLMs), AI agents, and enterprise integration patterns.
Key Responsibilities
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Design and implement Agentic AI solutions using AWS AI and Generative AI services.
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Develop autonomous AI agents capable of reasoning, planning, memory management, and task execution.
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Build multi-agent systems leveraging AWS services such as:
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Amazon Bedrock
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Amazon SageMaker
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AWS Lambda
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Amazon OpenSearch
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Amazon DynamoDB
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Amazon EventBridge
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Amazon API Gateway
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Create Retrieval Augmented Generation (RAG) architectures and knowledge-based AI assistants.
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Integrate AI agents with enterprise applications, APIs, databases, and business workflows.
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Develop prompt engineering strategies and agent orchestration logic.
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Design scalable, secure, and cost-optimized cloud architectures.
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Define observability, monitoring, governance, and Responsible AI practices.
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Collaborate with business stakeholders to translate AI use cases into technical solutions.
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Participate in architecture reviews, solution design workshops, and technical leadership activities.
Required Skills
AWS Cloud
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Amazon Bedrock
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Amazon SageMaker
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AWS Lambda
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AWS Step Functions
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Amazon API Gateway
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Amazon S3
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Amazon DynamoDB
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Amazon OpenSearch Service
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Event-driven architectures on AWS
AI / Generative AI
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Large Language Models (LLMs)
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Agentic AI concepts and architectures
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Multi-Agent Systems
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Prompt Engineering
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AI Planning and Reasoning
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Retrieval Augmented Generation (RAG)
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Vector Databases
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AI Evaluation Frameworks
Programming
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Python
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JavaScript / TypeScript
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REST APIs
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Microservices
DevOps & CI/CD
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Git
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Jenkins / GitHub Actions
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Docker
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Infrastructure as Code (Terraform or CloudFormation)
Preferred Qualifications
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AWS Certified Solutions Architect – Associate/Professional
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AWS Certified Machine Learning Engineer
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Hands-on experience with:
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LangGraph
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LangChain
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CrewAI
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AutoGen
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Semantic Kernel
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Amazon Bedrock Agents
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Experience implementing enterprise AI governance and security controls.
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Experience with GenAI use cases such as:
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Virtual Assistants
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IT Service Automation
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Knowledge Management
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Customer Support Automation
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AI-powered Software Development
Nice to Have
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Experience with ServiceNow AI capabilities.
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Knowledge of MCP (Model Context Protocol).
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Experience building AI copilots and enterprise search solutions.
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Knowledge of Responsible AI and AI Risk Management frameworks.
Education
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Bachelor's degree in Computer Science, Information Technology, Engineering, or related field.
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Master's degree preferred.
Key Competencies
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Strong problem-solving and analytical skills.
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Architecture and consulting mindset.
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Client-facing communication skills.
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Ability to lead technical discussions and mentor junior team members.
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Strong understanding of enterprise application integration patterns.