3 days ago
Responsibilities
- Define target architectures, security boundaries, integration patterns, deployment standards, reference architectures, and production-readiness standards for enterprise Agentic AI and Generative AI solutions.
- Lead architecture reviews covering security, scalability, resiliency, observability, performance, cost optimization, governance, and operational readiness.
- Design and implement AI agents, multi-agent workflows, LLM-based applications, RAG solutions, tool integrations, and model or agent orchestration on AWS.
- Design secure integrations between AI agents, enterprise applications, APIs, data platforms, knowledge sources, and external tools.
- Design and manage secure multi-account AWS environments using AWS Organizations, Control Tower, SCPs, IAM Identity Center, and shared services.
- Develop CI/CD pipelines and deploy containerized AgentCore and AI workloads using Docker, Amazon ECR, AWS CDK and/or Terraform.
- Configure AWS Systems Manager for operational automation and design data persistence using Amazon DynamoDB.
- Implement authentication, authorization, governance, guardrails, monitoring, observability, threat modeling, and responsible AI controls.
- Lead high-stakes discussions with senior leadership and collaborate with AI engineering, security, cloud, networking, data, and application teams.
Requirements
- Strong experience architecting and implementing Agentic AI and Generative AI solutions on AWS.
- Hands-on experience with AWS AgentCore, Amazon Bedrock, Amazon SageMaker, and related AWS AI/ML services.
- Experience taking AI/ML and Generative AI solutions from prototype or proof of concept through production deployment.
- Experience designing enterprise-grade systems for scalability, resiliency, security, performance, observability, and operational supportability.
- Experience with AWS Organizations, Control Tower, SCPs, IAM Identity Center, shared services, and secure multi-account environments.
- Experience with GitLab, GitHub, or Bitbucket CI/CD and AWS-native deployment services.
- Experience with Docker, Amazon ECR, AWS CDK and/or Terraform, AWS Systems Manager, and Amazon DynamoDB.
- Experience implementing OAuth/OBO authentication patterns and AWS Cedar authorization policies.
- Experience with AI guardrails, model governance, security controls, monitoring, compliance requirements, and responsible AI practices.
- Ability to lead architecture governance, security reviews, resiliency reviews, and senior-leadership conversations.
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About Cognizant
Cognizant is a public IT services and consulting firm that designs, builds, and runs enterprise technology, including digital engineering, cloud modernization, data/AI, and managed services. It sells consulting, systems integration, and outsourcing on multi-year engagements to large enterprises in healthcare, banking, retail, communications, and manufacturing. Founded in 1994 and headquartered in Teaneck, New Jersey, Cognizant is NASDAQ-listed (CTSH) and a Fortune 500 company.