Senior Specialist - Data Sciences (AWS Bedrock / Agentic AI)
TypeFull-time job
LocationIndia
Posted3 hours ago
Location: Hyderabad
Experience: 7–11 Years
About the Role
We are seeking an experienced AWS Agentic AI Architect with strong expertise in Amazon Bedrock and enterprise AI solution architecture. The role focuses on designing secure, scalable, and cost-effective Agentic AI, RAG, and LLM-powered solutions on AWS. You will work with business and technology stakeholders to translate requirements into AI-driven solutions and provide architecture and implementation guidance.
Job Description
The role involves designing and implementing Agentic AI solutions using AWS services, with deep expertise in Amazon Bedrock Foundation Models, Agents, Guardrails, and Knowledge Bases. You will develop intelligent agent solutions incorporating orchestration, planning, memory, tool integration, and enterprise system connectivity.
You will architect Knowledge Base-driven applications using vector databases and Retrieval-Augmented Generation (RAG), while integrating Bedrock Agents with APIs, databases, and business applications. The position requires strong understanding of LLM architectures, prompt engineering, agent workflows, autonomous AI systems, and cloud-native AI platform engineering.
The candidate will also establish governance, security, compliance, and responsible AI practices, perform technical assessments, and guide implementation teams. Strong communication and stakeholder management skills are required for architecture discussions, technical workshops, and cross-functional collaboration.
Key Responsibilities
Design and implement Agentic AI solutions using AWS services and Amazon Bedrock.
Architect solutions using Bedrock Foundation Models, Agents, Guardrails, and Knowledge Bases.
Develop agent orchestration capabilities covering planning, memory, and tool integrations.
Build enterprise RAG and Knowledge Base solutions using vector databases.
Integrate Bedrock Agents with enterprise APIs, databases, and business applications.
Design scalable, secure, and cost-optimized cloud-native AI architectures.
Establish AI governance, security, compliance, and responsible AI practices.
Conduct technical assessments, lead architecture discussions, and provide implementation guidance.
Required Skills
Amazon Bedrock
Agentic AI solution architecture and development
AWS AgentCore, including agent orchestration, planning, memory, and tool integration
RAG, Knowledge Bases, vector databases, and LLM integration
LLM architectures, prompt engineering, agent workflows, and autonomous AI systems
AWS cloud architecture and AI platform engineering
AWS services including Lambda, API Gateway, S3, DynamoDB, OpenSearch, ECS, EKS, IAM, and Step Functions
Enterprise API, database, and business application integration
AI governance, security, compliance, and responsible AI
Strong analytical, problem-solving, communication, and stakeholder management skills
AWS certification: AWS Certified Solutions Architect, AWS Certified AI Practitioner, AWS Certified Machine Learning Specialty, or equivalent
Preferred / Good to Have
Multi-agent systems and advanced AI orchestration frameworks
LangChain, LangGraph, CrewAI, Semantic Kernel, or AutoGen
Enterprise RAG using Amazon OpenSearch, Pinecone, Weaviate, or other vector databases
Model evaluation, observability, AI monitoring, and performance optimization
LLM fine-tuning, model customization, and prompt optimization
MLOps, CI/CD pipelines, and AI application deployment
Data engineering and structured/unstructured data integration
Responsible AI, AI governance, and compliance frameworks
Exposure to Azure OpenAI, Google Vertex AI, or other cloud AI platforms
Enterprise digital transformation and AI modernization initiatives
CX, conversational AI, chatbot, or virtual assistant solutions
Architecture workshops, technical leadership, and mentoring development teams
Preferred AWS certifications including AI Practitioner, Machine Learning Specialty, Solutions Architect Associate/Professional, or Developer Associate
Mandatory Skills
AWS Bedrock
Candidate Profile
The ideal candidate will have strong hands-on experience architecting and implementing Agentic AI solutions on AWS, with deep expertise in Amazon Bedrock and enterprise RAG architectures. The candidate should combine strong cloud and AI architecture skills with the ability to lead technical discussions, assess solutions, and communicate effectively with business and technology stakeholders.
Benefits Package
Competitive salary and benefits package
Opportunities for professional growth and development
A collaborative and inclusive work environment
The opportunity to work on exciting and challenging projects with leading clients
Originally posted on Himalayas
Experience: 7–11 Years
About the Role
We are seeking an experienced AWS Agentic AI Architect with strong expertise in Amazon Bedrock and enterprise AI solution architecture. The role focuses on designing secure, scalable, and cost-effective Agentic AI, RAG, and LLM-powered solutions on AWS. You will work with business and technology stakeholders to translate requirements into AI-driven solutions and provide architecture and implementation guidance.
Job Description
The role involves designing and implementing Agentic AI solutions using AWS services, with deep expertise in Amazon Bedrock Foundation Models, Agents, Guardrails, and Knowledge Bases. You will develop intelligent agent solutions incorporating orchestration, planning, memory, tool integration, and enterprise system connectivity.
You will architect Knowledge Base-driven applications using vector databases and Retrieval-Augmented Generation (RAG), while integrating Bedrock Agents with APIs, databases, and business applications. The position requires strong understanding of LLM architectures, prompt engineering, agent workflows, autonomous AI systems, and cloud-native AI platform engineering.
The candidate will also establish governance, security, compliance, and responsible AI practices, perform technical assessments, and guide implementation teams. Strong communication and stakeholder management skills are required for architecture discussions, technical workshops, and cross-functional collaboration.
Key Responsibilities
Design and implement Agentic AI solutions using AWS services and Amazon Bedrock.
Architect solutions using Bedrock Foundation Models, Agents, Guardrails, and Knowledge Bases.
Develop agent orchestration capabilities covering planning, memory, and tool integrations.
Build enterprise RAG and Knowledge Base solutions using vector databases.
Integrate Bedrock Agents with enterprise APIs, databases, and business applications.
Design scalable, secure, and cost-optimized cloud-native AI architectures.
Establish AI governance, security, compliance, and responsible AI practices.
Conduct technical assessments, lead architecture discussions, and provide implementation guidance.
Required Skills
Amazon Bedrock
Agentic AI solution architecture and development
AWS AgentCore, including agent orchestration, planning, memory, and tool integration
RAG, Knowledge Bases, vector databases, and LLM integration
LLM architectures, prompt engineering, agent workflows, and autonomous AI systems
AWS cloud architecture and AI platform engineering
AWS services including Lambda, API Gateway, S3, DynamoDB, OpenSearch, ECS, EKS, IAM, and Step Functions
Enterprise API, database, and business application integration
AI governance, security, compliance, and responsible AI
Strong analytical, problem-solving, communication, and stakeholder management skills
AWS certification: AWS Certified Solutions Architect, AWS Certified AI Practitioner, AWS Certified Machine Learning Specialty, or equivalent
Preferred / Good to Have
Multi-agent systems and advanced AI orchestration frameworks
LangChain, LangGraph, CrewAI, Semantic Kernel, or AutoGen
Enterprise RAG using Amazon OpenSearch, Pinecone, Weaviate, or other vector databases
Model evaluation, observability, AI monitoring, and performance optimization
LLM fine-tuning, model customization, and prompt optimization
MLOps, CI/CD pipelines, and AI application deployment
Data engineering and structured/unstructured data integration
Responsible AI, AI governance, and compliance frameworks
Exposure to Azure OpenAI, Google Vertex AI, or other cloud AI platforms
Enterprise digital transformation and AI modernization initiatives
CX, conversational AI, chatbot, or virtual assistant solutions
Architecture workshops, technical leadership, and mentoring development teams
Preferred AWS certifications including AI Practitioner, Machine Learning Specialty, Solutions Architect Associate/Professional, or Developer Associate
Mandatory Skills
AWS Bedrock
Candidate Profile
The ideal candidate will have strong hands-on experience architecting and implementing Agentic AI solutions on AWS, with deep expertise in Amazon Bedrock and enterprise RAG architectures. The candidate should combine strong cloud and AI architecture skills with the ability to lead technical discussions, assess solutions, and communicate effectively with business and technology stakeholders.
Benefits Package
Competitive salary and benefits package
Opportunities for professional growth and development
A collaborative and inclusive work environment
The opportunity to work on exciting and challenging projects with leading clients
Originally posted on Himalayas
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