Job description

Position Summary The AI Platform Strategist is responsible for defining and driving the enterprise AI platform vision, strategy, and roadmap on AWS. This role serves as the bridge between business leadership, data teams, cloud engineering, architecture, and AI practitioners to design a scalable, secure, and governed AI ecosystem that accelerates innovation and business value. The strategist leads platform planning activities, assesses current-state AI and data capabilities, defines future-state architectures, establishes governance frameworks, and develops implementation roadmaps for AI, Generative AI, Agentic AI, and advanced analytics solutions built on AWS. Key Responsibilities AI Platform Strategy & Roadmap • Define the enterprise AI platform vision and target operating model. • Develop multi-year AI platform roadmaps aligned to business and technology objectives. • Assess current AI, data, analytics, and cloud capabilities. • Identify platform gaps, dependencies, and modernization priorities. • Establish phased implementation plans and investment recommendations. AWS AI & Data Architecture Strategy • Define target-state AI platform architecture leveraging AWS services. • Develop architecture patterns for: • Generative AI • Agentic AI • Machine Learning • Data Science Workbenches • Model Lifecycle Management • AI Application Development • Establish design principles for scalability, interoperability, security, and reusability. • Guide integration of AI capabilities with enterprise applications and business workflows. AI Services & Platform Capability Development Lead strategy for platform capabilities including: • Amazon Bedrock • Amazon SageMaker • AWS Glue • Amazon EMR • Amazon Redshift • Amazon OpenSearch • Amazon Kendra • Amazon EKS • AWS Lambda • AWS Step Functions Define platform services such as: • Prompt Management • Model Catalogs • Feature Stores • Vector Databases • RAG Frameworks • Agent Orchestration • MLOps • LLMOps • API Management • AI Monitoring and Observability AI Governance & Responsible AI • Define AI governance frameworks and operational controls. • Establish model governance and lifecycle management processes. • Create policies for: • Responsible AI • Data Privacy • Security • Compliance • Risk Management • Define AI guardrails and human-in-the-loop review processes. • Align platform capabilities with industry and regulatory requirements. Demand Management & Use Case Prioritization • Design frameworks for intake, assessment, and prioritization of AI opportunities. • Create value-based scoring methodologies. • Align business demand with platform capabilities and implementation capacity. • Develop repeatable processes for onboarding new AI use cases. • Maintain enterprise AI opportunity portfolios and roadmaps. Operating Model & Organizational Readiness • Define AI platform ownership and organizational structures. • Establish AI Centers of Excellence (CoE). • Develop platform support and service models. • Recommend talent, skills, and capability-building strategies. • Drive adoption and change management initiatives. Executive Advisory • Advise executive stakeholders on AI platform investments and priorities. • Present AI strategy, architecture, and roadmap recommendations. • Develop board-level and executive business cases. • Align platform initiatives to measurable business outcomes and ROI. Required Qualifications • 10+ years of experience in enterprise architecture, cloud strategy, data strategy, AI strategy, or digital transformation. • 5+ years working with AWS cloud technologies. • Experience designing enterprise AI or data platforms. • Strong understanding of: • Generative AI • Agentic AI • Machine Learning • Data Platforms • MLOps and LLMOps • Cloud-Native Architectures • Experience developing executive-level roadmaps and business cases. • Strong communication and stakeholder management skills. Preferred Qualifications AWS Certifications • AWS Certified Solutions Architect Professional • AWS Certified Machine Learning Specialty • AWS Certified Data Engineer • AWS Certified AI Practitioner Industry Experience • Healthcare • Payer • Provider • Life Sciences • Highly regulated industries Additional Experience • Databricks • Snowflake • Collibra • Informatica • Data Governance Platforms • AI Governance Platforms Key Deliverables • Enterprise AI Platform Strategy • AWS AI Reference Architecture • AI Capability Assessment • AI Maturity Assessment • Platform Roadmap (12-36 Months) • AI Governance Framework • Responsible AI Framework • AI Operating Model • Use Case Prioritization Framework • AI Service Catalog • MLOps/LLMOps Strategy Business Value Realization Framework We're excited to meet people who share our mission and can make an impact in a variety of ways. Don't hesitate to apply, even if you only meet the minimum requirements listed. Think about your transferable experiences and unique skills that make you stand out as someone who can bring new and exciting things to this role. Salary and Other Compensation: Applications will be accepted until Nov 15, 2026. The annual salary for this position is between $80,000 - $180,000 depending on experience and other qualifications of the successful candidate. This position is also eligible for Cognizant’s discretionary annual incentive program, based on performance and subject to the terms of Cognizant’s applicable plans. Benefits: Cognizant offers the following benefits for this position, subject to applicable eligibility requirements: • Medical/Dental/Vision/Life Insurance • Paid holidays plus Paid Time Off • 401(k) plan and contributions • Long-term/Short-term Disability • Paid Parental Leave • Employee Stock Purchase Plan Disclaimer: The salary, other compensation, and benefits 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. 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

AI Platform Strategy & Roadmap
Define the enterprise AI platform vision and target operating model.
Develop multi-year AI platform roadmaps aligned to business and technology objectives.
Assess current AI, data, analytics, and cloud capabilities.
Identify platform gaps, dependencies, and modernization priorities.
Establish phased implementation plans and investment recommendations.
AWS AI & Data Architecture Strategy
Define target-state AI platform architecture leveraging AWS services.
Develop architecture patterns for: • Generative AI
Machine Learning
Data Science Workbenches
Model Lifecycle Management
AI Application Development
Establish design principles for scalability, interoperability, security, and reusability.
Guide integration of AI capabilities with enterprise applications and business workflows.
AI Services & Platform Capability Development
Lead strategy for platform capabilities including:
Amazon Bedrock
Amazon SageMaker
Amazon Redshift
Amazon OpenSearch
Amazon Kendra
AWS Step Functions
Prompt Management

Nice-to-haves

None flagged.

Application prep

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

Keywords to mirror

aiawsmachine learningapi

Platform: cognizant
Effort: medium

Benefits

Benefits detected in the listing.

Dental

Vision

401(K)

Paid Time Off

Parental Leave