Job Title: AWS Bedrock Agentic AI Solutions Architect
Location: Hyderabad – Preferred (Pan India)
No. of Resume Required: 3
Years of Experience: 6+ Years

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

Function

Cloud & AI Engineering – Agentic AI Solutions on AWS (Bedrock / AgentCore)

Role Summary

We are looking for an AWS Bedrock Agentic AI Solutions Architect to design and implement enterprise-grade Agentic AI solutions on AWS. The role requires strong hands-on expertise in Amazon Bedrock, AWS AgentCore, Knowledge Bases, and Retrieval-Augmented Generation (RAG), along with the ability to architect scalable, secure, and cost-optimized cloud-native AI solutions. The candidate will define AI solution architecture, guide implementation, and integrate Bedrock Agents with enterprise systems, APIs, and business applications.

Key Responsibilities

• Design and implement Agentic AI solutions using AWS services, including Amazon Bedrock and AWS AgentCore.
• Build Knowledge Base-driven AI applications using vector databases and Retrieval-Augmented Generation (RAG).
• Integrate Bedrock Agents with enterprise systems, APIs, databases, and business applications.
• Define AI solution architecture, perform technical assessments, and provide implementation guidance.
• Design agent orchestration, planning, memory, and tool integrations using AWS AgentCore.
• Architect scalable, secure, and cost-optimized cloud-native AI solutions on AWS.
• Implement governance, security, compliance, and responsible AI practices across AI solutions.
• Lead architecture discussions and technical workshops, and mentor development teams.

Primary Skills (Must Have)

AWS Bedrock & Agentic AI

• Amazon Bedrock – Foundation Models, Agents, Guardrails, and Knowledge Bases.
• AWS AgentCore – agent orchestration, planning, memory, and tool integrations.
• Hands-on design and implementation of Agentic AI solutions on AWS.

AI / LLM / RAG

• Knowledge Base-driven AI applications using vector databases and RAG.
• LLM architectures, prompt engineering, agent workflows, and autonomous AI systems.

AWS Core Services

• Lambda
• API Gateway
• S3
• DynamoDB
• OpenSearch
• ECS
• EKS
• IAM
• Step Functions

Architecture, Governance & Security

• Designing scalable, secure, and cost-optimized cloud-native AI solutions.
• Governance, security, compliance, and responsible AI practices.
• Technical assessments and AI solution architecture definition.

Secondary Skills (Nice to Have)

• Experience with multi-agent systems and advanced AI orchestration frameworks.
• Hands-on exposure to LangChain, LangGraph, CrewAI, Semantic Kernel, AutoGen, or similar agent frameworks.
• Experience building enterprise-grade RAG solutions using Amazon OpenSearch, Pinecone, Weaviate, or other vector databases.
• Knowledge of model evaluation, observability, AI monitoring, and performance optimisation.
• Experience with LLM fine-tuning, model customisation, and prompt optimisation techniques.
• Familiarity with MLOps, CI/CD pipelines, and AI application deployment strategies.
• Experience with data engineering and integrating structured/unstructured data sources into AI solutions.
• Knowledge of Responsible AI, AI governance, and compliance frameworks.
• Exposure to Azure OpenAI, Google Vertex AI, or other cloud AI platforms.
• Experience working on enterprise digital transformation and AI modernisation initiatives.
• Understanding of customer experience (CX), conversational AI, chatbot, and virtual assistant solutions.
• Experience leading architecture discussions, technical workshops, and mentoring development teams.

Key Competencies

• Strong problem-solving and analytical skills, with the ability to translate business requirements into AI-driven solutions.
• Excellent communication and stakeholder management skills.
• Ability to lead architecture discussions and mentor development teams.

Experience & Qualifications

• 6+ years of overall experience, with strong hands-on expertise in Amazon Bedrock, AWS AgentCore, and Agentic AI solution design.
• AWS Certification is mandatory: AWS Certified Solutions Architect, AWS Certified AI Practitioner, AWS Certified Machine Learning – Specialty, or equivalent.

Preferred Certifications

• AWS Certified AI Practitioner
• AWS Certified Machine Learning – Specialty
• AWS Certified Solutions Architect – Associate/Professional
• AWS Certified Developer – Associate

Ways of Working

• Working Mode: Hybrid – 3 days from office.
• Work Timing: 12:00 PM – 9:30 PM IST.
• Location: Hyderabad – Preferred (Pan India).