AWS Agentic AI Architect – AWS Bedrock Specialist

e are looking for an experienced AWS Agentic AI Architect to design, develop, and implement enterprise-grade AI solutions using Amazon Bedrock and AWS cloud services. The ideal candidate will have strong expertise in intelligent agent development, agent orchestration, Knowledge Bases, Retrieval-Augmented Generation (RAG), and large language model (LLM) integration.

The role involves defining AI solution architectures, integrating intelligent agents with enterprise systems, and ensuring that AI solutions are scalable, secure, cost-effective, and compliant with organizational standards.

Primary Skills

• AWS Bedrock Agentic AI Solutions
• AWS AgentCore
• Knowledge Bases
• Intelligent Agent Development

Secondary Skills

• Generative AI
• RAG Architecture
• LLM Integration
• Cloud Architecture
• AWS Services
• AI Platform Engineering

Key Responsibilities1. Agentic AI Architecture and Development

• Design and implement Agentic AI solutions using AWS services.
• Develop intelligent agents capable of planning, orchestration, memory management, and tool integration.
• Define AI solution architectures based on business and technical requirements.
• Perform technical assessments and provide implementation guidance to development teams.

1. Amazon Bedrock and AgentCore

• Build AI solutions using Amazon Bedrock Foundation Models, Agents, Guardrails, and Knowledge Bases.
• Use AWS AgentCore capabilities to support agent orchestration and intelligent agent workflows.
• Integrate AI agents with enterprise APIs, databases, and business applications.
• Design secure and reliable agent workflows for enterprise use cases.

1. RAG and Knowledge-Based Applications

• Build Knowledge Base-driven AI applications using vector databases and RAG architectures.
• Integrate structured and unstructured data sources into AI applications.
• Develop solutions that improve knowledge retrieval and response relevance.
• Work with Amazon OpenSearch, Pinecone, Weaviate, or similar vector database technologies.

1. AWS Cloud Architecture

• Design scalable, secure, and cost-optimized cloud-native AI solutions.
• Work with AWS services, including:
• AWS Lambda
• Amazon API Gateway
• Amazon S3
• Amazon DynamoDB
• Amazon OpenSearch
• Amazon ECS and EKS
• AWS IAM
• AWS Step Functions
• Ensure AI applications follow cloud architecture and security best practices.

1. AI Security, Governance, and Compliance

• Implement governance, security, compliance, and responsible AI practices.
• Apply appropriate controls to AI workflows, data access, and enterprise integrations.
• Support AI solution assessments and address technical and operational risks.
• Consider model evaluation, observability, performance, and cost optimization.

1. Stakeholder Collaboration

• Translate business requirements into practical AI-driven solutions.
• Lead architecture discussions and technical workshops.
• Collaborate with business stakeholders, architects, and development teams.
• Provide technical guidance and mentor development teams where required.

Mandatory Skills and Qualifications

• Minimum 6 years of relevant professional experience.
• Hands-on experience designing and implementing Agentic AI solutions using AWS services.
• Strong expertise in Amazon Bedrock, including Foundation Models, Agents, Guardrails, and Knowledge Bases.
• Experience with AWS AgentCore, including agent orchestration, planning, memory, and tool integrations.
• Proven experience building RAG-based AI applications using vector databases.
• Strong understanding of LLM architectures, prompt engineering, agent workflows, and autonomous AI systems.
• Experience integrating Bedrock Agents with enterprise systems, APIs, databases, and business applications.
• Strong knowledge of AWS cloud architecture and services.
• Experience implementing AI security, governance, compliance, and responsible AI practices.
• Excellent problem-solving, analytical, communication, and stakeholder management skills.
• Mandatory certification: AWS Certified Solutions Architect, AWS Certified AI Practitioner, AWS Certified Machine Learning – Specialty, or an equivalent certification.

Good-to-Have Skills

• Experience with multi-agent systems and advanced AI orchestration frameworks.
• Hands-on experience with LangChain, LangGraph, CrewAI, Semantic Kernel, AutoGen, or similar frameworks.
• Experience building enterprise-grade RAG solutions using Amazon OpenSearch, Pinecone, Weaviate, or other vector databases.
• Knowled…