AWS Bedrock Agentic AI Solutions Architect

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 solid 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).

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 AWS Bedrock Agentic AI Solutions Architect (Hyderabad)
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