Job description

Job Summary We are looking for strong AI Technical Architect to drive our innovation strategy using Amazon Web Services. This role focuses on building sophisticated, autonomous AI agents using AWS Bedrock. You will be the primary technical authority on Agentic AI, responsible for designing systems where Foundation Models (FMs) interact intelligently with enterprise data and APIs to perform complex tasks. You will lead high-stakes conversations with senior leadership to define the "Art of the Possible" regarding GenAI. Architecture & Platform Leadership • Define target architecture, security boundaries, integration patterns, and deployment standards for enterprise Agentic AI and Generative AI solutions . • Lead architecture reviews covering security, scalability, resiliency, observability, performance, and cost optimization. • Establish reusable platform patterns, golden-path templates, reference architectures, and production-readiness standards. • Collaborate with AI engineering, security, cloud, networking, data, and application teams to drive secure and governed adoption of AI capabilities. • Provide architecture governance, production-readiness oversight, and leadership for security and resiliency reviews. Agentic AI & AWS AI/ML • 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 designing AI agents, multi-agent workflows, LLM-based applications, RAG solutions, tool integration, and model/agent orchestration . • Design secure integration patterns between AI agents, enterprise applications, APIs, data platforms, knowledge sources, and external tools. • Experience implementing AI guardrails, security controls, model governance, observability, monitoring, and responsible AI practices . • Experience taking AI/ML and Generative AI solutions from prototype/PoC through production deployment . • Design Agentic AI solutions for enterprise-grade scalability, resiliency, security, performance, and operational supportability . Cloud Engineering & DevSecOps • Design and manage secure multi-account AWS environments using AWS Organizations, Control Tower, SCPs, IAM Identity Center , and shared services. • Develop and manage CI/CD pipelines using GitLab, GitHub, or Bitbucket CI/CD and AWS-native deployment services. • Build, package, and deploy AgentCore and AI workloads as containerized applications using Docker and Amazon ECR . • Implement Infrastructure as Code (IaC) using AWS CDK and/or Terraform , including automated deployment pipelines. • Configure and manage AWS Systems Manager (SSM) for operational automation. • Design and optimize data persistence using Amazon DynamoDB . • Implement secure authentication and authorization using OAuth/OBO patterns . • Apply security and governance policies using the AWS Cedar authorization framework . • Support threat modeling, security reviews, compliance requirements, and production-readiness assessments. • Ensure model, agent, and tool interactions follow approved governance and security controls, including deny-by-default Cedar policies, guardrails, private connectivity, identity controls, and secure access patterns . Additional employment information Compensation information is accurate as of the date of this posting. Cognizant reserves the right to modify this information at any time, subject to applicable law. Applicants may be required to attend interviews in person or by video conference. In addition, candidates may be required to present their current state or government issued ID during each interview. Cognizant is an equal opportunity employer. Your application and candidacy will not be considered based on race, color, sex, religion, creed, sexual orientation, gender identity, national origin, disability, genetic information, pregnancy, veteran status or any other characteristic protected by federal, state or local laws. Applicants for US based positions must be currently authorized to work for any employer in the United States. The company is unable to provide employment-based immigration sponsorship for US based positions. If you have a disability that requires reasonable accommodation to search for a job opening or submit an application, please email CareersNA2@cognizant.com for roles based in the Americas or CareersIndia2@cognizant.com for roles based in India. About Cognizant: Cognizant (Nasdaq: CTSH) is an AI Builder and technology services provider, bridging the gap between AI investment and enterprise value by building full-stack AI solutions for our clients. Our deep industry, process and engineering expertise enables us to build an organization’s unique context into technology systems that amplify human potential, drive tangible outcomes and keep global enterprises ahead in a fast-changing world. See how at cognizant.ai or @cognizant.

Requirements

Must-haves

Architecture & Platform Leadership
Define target architecture, security boundaries, integration patterns, and deployment standards for enterprise Agentic AI and Generative AI solutions .
Lead architecture reviews covering security, scalability, resiliency, observability, performance, and cost optimization.
Establish reusable platform patterns, golden-path templates, reference architectures, and production-readiness standards.
Collaborate with AI engineering, security, cloud, networking, data, and application teams to drive secure and governed adoption of AI capabilities.
Provide architecture governance, production-readiness oversight, and leadership for security and resiliency reviews.
Agentic AI & AWS AI/ML
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 designing AI agents, multi-agent workflows, LLM-based applications, RAG solutions, tool integration, and model/agent orchestration .
Design secure integration patterns between AI agents, enterprise applications, APIs, data platforms, knowledge sources, and external tools.
Experience implementing AI guardrails, security controls, model governance, observability, monitoring, and responsible AI practices .
Experience taking AI/ML and Generative AI solutions from prototype/PoC through production deployment .
Design Agentic AI solutions for enterprise-grade scalability, resiliency, security, performance, and operational supportability .
Cloud Engineering & DevSecOps
Design and manage secure multi-account AWS environments using AWS Organizations, Control Tower, SCPs, IAM Identity Center , and shared services.
Develop and manage CI/CD pipelines using GitLab, GitHub, or Bitbucket CI/CD and AWS-native deployment services.
Build, package, and deploy AgentCore and AI workloads as containerized applications using Docker and Amazon ECR .
Implement Infrastructure as Code (IaC) using AWS CDK and/or Terraform , including automated deployment pipelines.
Configure and manage AWS Systems Manager (SSM) for operational automation.
Design and optimize data persistence using Amazon DynamoDB .
Implement secure authentication and authorization using OAuth/OBO patterns .
Apply security and governance policies using the AWS Cedar authorization framework .
Support threat modeling, security reviews, compliance requirements, and production-readiness assessments.

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aiawsmlllmci/cddocker

Platform: cognizant
Effort: medium