Senior Specialist - Architecture
TypeFull-time job
LocationIndia
Posted2 hours ago
Location: Hyderabad
Experience: 7–11 Years
About the Role
We are seeking a hands-on AWS AI/ML Architect or Lead with strong experience in Generative AI, multi-agent systems, and distributed application architecture. The role focuses on designing and deploying production-scale agentic solutions using Amazon Bedrock AgentCore, Amazon SageMaker, Python/TypeScript, and modern agent frameworks.
Job Description
The role involves architecting autonomous, multi-step agentic workflows that integrate with enterprise data, APIs, and business systems. The candidate will help transition agentic applications from local environments to production using AWS AgentCore Runtime and related managed services.
The position requires strong expertise in enterprise security, identity management, observability, API integration, and agent orchestration. The architect will also work with frameworks such as LangGraph, CrewAI, and LlamaIndex, ensuring scalable and secure deployment.
Key Responsibilities
Design and build autonomous, multi-step agentic workflows for enterprise applications.
Architect distributed multi-agent systems using AWS AgentCore for runtime isolation, long-running workloads, and memory/context awareness.
Integrate legacy APIs and AWS Lambda functions as agent-ready tools using AgentCore Gateway and Model Context Protocol (MCP).
Design end-to-end security controls using AWS IAM, encryption, API management, and AgentCore Identity capabilities.
Implement authentication, role-based access controls, and policy guardrails for AI pipelines.
Establish real-time telemetry, tracing, observability, and continuous agent evaluation processes.
Support open-source orchestration frameworks such as LangGraph and CrewAI with production deployment through the AgentCore CLI.
Collaborate with technical teams and stakeholders through presentations, solution discussions, and architecture reviews.
Required Skills
AWS AI/ML Services
Amazon Bedrock AgentCore
Amazon SageMaker
Generative AI and Multi-Agent Systems
Distributed application architecture
Python or TypeScript
CrewAI, LangGraph, or LlamaIndex
AWS security, IAM, encryption, and API management
AgentCore Runtime, Gateway, Identity, and CLI
Model Context Protocol (MCP)
Agent observability, telemetry, and evaluation
Mandatory Skills
AWS AI Services
Candidate Profile
Bachelor's degree with approximately 10 years of experience in designing distributed applications, including at least 3 years of strong focus on Generative AI and multi-agent systems. The ideal candidate will have hands-on AWS AI/ML expertise, strong AgentCore implementation experience, and the ability to design secure, production-ready agentic architectures while effectively collaborating with enterprise teams.
Originally posted on Himalayas
Experience: 7–11 Years
About the Role
We are seeking a hands-on AWS AI/ML Architect or Lead with strong experience in Generative AI, multi-agent systems, and distributed application architecture. The role focuses on designing and deploying production-scale agentic solutions using Amazon Bedrock AgentCore, Amazon SageMaker, Python/TypeScript, and modern agent frameworks.
Job Description
The role involves architecting autonomous, multi-step agentic workflows that integrate with enterprise data, APIs, and business systems. The candidate will help transition agentic applications from local environments to production using AWS AgentCore Runtime and related managed services.
The position requires strong expertise in enterprise security, identity management, observability, API integration, and agent orchestration. The architect will also work with frameworks such as LangGraph, CrewAI, and LlamaIndex, ensuring scalable and secure deployment.
Key Responsibilities
Design and build autonomous, multi-step agentic workflows for enterprise applications.
Architect distributed multi-agent systems using AWS AgentCore for runtime isolation, long-running workloads, and memory/context awareness.
Integrate legacy APIs and AWS Lambda functions as agent-ready tools using AgentCore Gateway and Model Context Protocol (MCP).
Design end-to-end security controls using AWS IAM, encryption, API management, and AgentCore Identity capabilities.
Implement authentication, role-based access controls, and policy guardrails for AI pipelines.
Establish real-time telemetry, tracing, observability, and continuous agent evaluation processes.
Support open-source orchestration frameworks such as LangGraph and CrewAI with production deployment through the AgentCore CLI.
Collaborate with technical teams and stakeholders through presentations, solution discussions, and architecture reviews.
Required Skills
AWS AI/ML Services
Amazon Bedrock AgentCore
Amazon SageMaker
Generative AI and Multi-Agent Systems
Distributed application architecture
Python or TypeScript
CrewAI, LangGraph, or LlamaIndex
AWS security, IAM, encryption, and API management
AgentCore Runtime, Gateway, Identity, and CLI
Model Context Protocol (MCP)
Agent observability, telemetry, and evaluation
Mandatory Skills
AWS AI Services
Candidate Profile
Bachelor's degree with approximately 10 years of experience in designing distributed applications, including at least 3 years of strong focus on Generative AI and multi-agent systems. The ideal candidate will have hands-on AWS AI/ML expertise, strong AgentCore implementation experience, and the ability to design secure, production-ready agentic architectures while effectively collaborating with enterprise teams.
Originally posted on Himalayas
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