8-10 years of experience in AI architecture and development.
Strong experience with AWS AgentCore, Context Engineering, and Harness Engineering.
Proficiency in Python development for backend services.
Hands-on experience with multi-agent orchestration and proactive AI automation.
Familiarity with enterprise knowledge ingestion and retrieval pipelines.
Experience with containerization and deployment on Amazon EKS.
Knowledge of security and access management practices.
Responsibilities
Design and build intelligent AI agents for complex workflows with minimal human intervention.
Utilize AWS AgentCore for agent deployment, focusing on various capabilities like Runtime and Observability.
Develop effective context management strategies for memory retrieval and conversation summarization.
Build reliable frameworks for agent execution, including tool-call orchestration and automated testing.
Create event-driven agents for proactive automation and workflow initiation.
Develop knowledge ingestion pipelines using PostgreSQL and RAG techniques.
Establish agent evaluation and monitoring systems to ensure performance and security.
Benefits
Opportunity to work on cutting-edge AI technologies and solutions.
Hands-on role with ownership of the complete development lifecycle.
Focus on rapid delivery and engineering quality.
Collaborative environment with a strong emphasis on innovation.
Access to advanced tools and frameworks for AI development.
Full Job Description
Role Overview:
The Senior Agentic AI Architect will design, build, and deploy enterprise-grade AI assistants and intelligent automation solutions, focusing on AWS AgentCore, Context Engineering, and Harness Engineering. This hands-on role involves owning the complete development lifecycle, from solution design and implementation to deployment and optimization, with a strong emphasis on rapid delivery and engineering quality.
Key Responsibilities:
Design and build intelligent AI agents capable of reasoning, planning, tool execution, and managing complex workflows with minimal human intervention.
Utilize AWS AgentCore for building and deploying agents, including Runtime, Memory, Gateway, Identity, Policy, and Observability capabilities.
Build reliable agent execution frameworks with tool-call orchestration, retry handling, structured output validation, capability routing, and automated testing.
Develop and coordinate specialized AI agents using frameworks such as LangGraph or Strands Agents, including task delegation, state management, and workflow execution.
Build event-driven agents for proactive AI automation, monitoring activities, generating notifications, drafting communications, and initiating authorized workflows.
Develop knowledge ingestion and retrieval pipelines using PostgreSQL, pgvector, and RAG techniques, with appropriate knowledge governance and access controls.
Build MCP servers and clients to connect agents with enterprise applications, APIs, communication platforms, and internal knowledge systems.
Design and implement solutions using AWS IAM, Secrets Manager, ECR, Aurora PostgreSQL, SQS, EventBridge, and CloudWatch.
Deploy and manage FastAPI and Next.js applications on Amazon EKS using Docker, Kubernetes, Helm, autoscaling, ingress, and AgentCore connectivity.
Develop backend services using Python/FastAPI and frontend applications using Next.js and TypeScript.
Implement enterprise SSO, Cedar/ABAC policies, fine-grained authorization, secure data handling, and protection against unauthorized agent actions.
Implement approval mechanisms and user controls for AI-generated communications, recommendations, and sensitive automated actions.
Build persistent memory, personalized context, conversation continuity, and reliable asynchronous workflows with checkpointing and failure recovery.
Establish agent evaluation, execution tracing, monitoring, logging, and testing to ensure accuracy, reliability, security, and performance.
Take ownership of architecture, hands-on development, integration, testing, and deployment, with a strong focus on practical solutions, engineering quality, and rapid delivery.
Required Skills:
Strong experience in AWS AgentCore, Context Engineering, and Harness Engineering.
Proficiency in Python development.
Familiarity with multi-agent orchestration and proactive AI automation.
Experience in building production-ready agentic systems.
Hands-on experience building and deploying agents using AWS AgentCore, including Runtime, Memory, Gateway, Identity, Policy, and Observability capabilities.
AWS - Bedrock.
Knowledge of enterprise knowledge ingestion and retrieval pipelines.
Familiarity with security and access management practices.
Experience with containerization and deployment on EKS.
