Agentic AI Architect – AWS

Agentic AI Architect – AWS

Summary

This pivotal role is dedicated to designing and orchestrating sophisticated multi-agent systems within the AWS ecosystem, leveraging cutting-edge Agentic AI principles. The successful candidate will drive the strategic implementation of autonomous agents capable of complex task execution, ensuring seamless interaction between systems through advanced communication protocols. This position is critical for advancing the organization's capabilities in generative AI, focusing on building resilient, scalable, and cost-effective architectures that support next-generation intelligent applications.

Responsibilities

• Architect and deploy robust multi-agent frameworks utilizing AWS Bedrock to enable autonomous decision-making and task delegation.
  
• Engineer secure communication channels between agents, implementing function calling mechanisms to facilitate precise tool usage and data exchange.
  
• Develop and maintain comprehensive evaluation frameworks and observability solutions to monitor agent performance, ensuring adherence to safety guardrails and operational standards.
  
• Optimize system performance by minimizing latency while balancing computational costs and maximizing overall reliability for production environments.
  
• Conduct in-depth AI and Generative AI research to identify emerging trends and integrate innovative methodologies into the existing architecture.
  
• Lead the design of end-to-end Agentic AI solutions that align with business objectives and technical scalability requirements.
  

RequirementsRequirements:

• Minimum of 12 years of professional experience in software architecture, with a strong focus on cloud-native solutions.
  
• Proven expertise in Agentic AI architecture, specifically in designing and managing complex multi-agent systems.
  
• Deep technical proficiency in Agent-to-Agent communication patterns and the implementation of function calling mechanisms.
  
• Strong background in establishing guardrails, evaluation frameworks, and observability tools for AI-driven applications.
  
• Demonstrated ability to optimize AI systems for low latency, cost-efficiency, and high reliability.
  
• Extensive hands-on experience with AWS Bedrock and related services within the AWS ecosystem.
  
• Solid foundation in AI and Generative AI research, with the ability to translate theoretical concepts into practical, scalable solutions.