AWS Architect

Seeking an experienced AWS Agentic AI Architect to design and implement enterprise-grade Agentic AI solutions using Amazon Bedrock, AWS AgentCore, Knowledge Bases, and

RAG architectures. The role involves solution architecture, intelligent agent development, cloud integration, security, and performance optimization.

Key Responsibilities

Design and implement Agentic AI solutions using Amazon Bedrock Foundation Models, Agents, Guardrails, and Knowledge Bases.

Develop intelligent agents using AgentCore, including orchestration, planning, memory, and tool integration.

Build RAG-based applications using vector databases and integrate AI agents with enterprise APIs, databases, and business systems.

Architect scalable, secure, and cost-optimized AI solutions using AWS services.

Implement AI governance, security, compliance, and responsible AI practices.

Define solution architecture, conduct technical assessments, guide implementation, and collaborate with stakeholders.

Mandatory Skills

6+ years of relevant experience in cloud, AI architecture, or solution development.

Hands-on experience designing and implementing Agentic AI solutions on AWS.

Strong expertise in Amazon Bedrock, including Foundation Models, Agents, Guardrails, and Knowledge Bases.

Knowledge of AWS AgentCore, agent orchestration, planning, memory, and tool integration.

Experience building RAG applications using vector databases.

Strong understanding of LLM architectures, prompt engineering, agent workflows, and autonomous AI systems.

Experience integrating AI agents with enterprise systems, APIs, and databases.

Knowledge of AWS Lambda, API Gateway, S3, DynamoDB, OpenSearch, ECS/EKS, IAM, and Step Functions.

Expertise in cloud-native AI architecture, security, governance, and cost optimization.

Strong analytical, problem-solving, communication, and stakeholder-management skills.

Mandatory AWS certification: AWS Certified Solutions Architect, AWS Certified AI Practitioner, AWS Certified Machine Learning – Specialty, or equivalent certification.

Good to Have

Multi-agent systems and frameworks: LangChain, LangGraph, CrewAI, Semantic Kernel, or AutoGen.

Enterprise RAG solutions using Amazon OpenSearch, Pinecone, Weaviate, or similar vector databases.

Model evaluation, AI observability, monitoring, performance optimization, and prompt tuning.

LLM fine-tuning, MLOps, CI/CD, and AI application deployment.

Data engineering and integration of structured and unstructured data.

Responsible AI, AI governance, and compliance frameworks.

Exposure to Azure OpenAI, Google Vertex AI, conversational AI, chatbots, or virtual assistants.

Experience leading architecture discussions, technical workshops, and mentoring teams.

Preferred Certifications

AWS Certified AI Practitioner

AWS Certified Machine Learning – Specialty

AWS Certified Solutions Architect – Associate/Professional

AWS Certified Developer – Associate

Mandatory Skills – Quick Screening

AWS Bedrock | AgentCore | Agentic AI | RAG | Foundation Models | Bedrock Agents | Guardrails | Knowledge Bases | Vector Databases | AWS Cloud Architecture | AWS Certification