- 7to 15 years of overall IT experience.
- Minimum 3+ years in Enterprise Architecture, AI Architecture, or Digital Transformation leadership roles.
- Proven experience designing and deploying enterprise-scale AI and Generative AI solutions.
- Experience leading large-scale technology transformation programs across multiple business domains.
- Strong experience working directly with executive stakeholders and client architecture boards.
- Agentic AI
- Generative AI
- AI Functional Architecture
- Enterprise Architecture
- Responsible AI
- Large Language Models (LLMs)
- Retrieval-Augmented Generation (RAG)
- Multi-Agent Systems
- AI Governance & Compliance
- Cloud-native AI Architectures
- AI Platform Strategy
- Enterprise Digital Transformation
- AI Strategy & Governance
- Regulated Business Processes
- Human-in-the-Loop AI Systems
- Financial Services
- Healthcare & Life Sciences
- Insurance
- Regulatory Technology
- Cloud Platforms (Azure, AWS, GCP)
- AI Security & Risk Management
- MLOps and AI Operations
- Design AI-native enterprise architectures for large transformation programs.
- Define human-agent capability matrices and operating models for AI-enabled delivery.
- Architect multi-agent ecosystems that integrate enterprise applications, data platforms, and business processes.
- Develop scalable context engineering and knowledge orchestration frameworks.
- Define guardrails, policies, and boundary specifications for agentic AI systems.
- Establish governance models for AI autonomy, decision-making, and escalation controls.
- Design human oversight mechanisms for enterprise AI operations.
- Create standards for AI system traceability, transparency, and auditability.
- Architect Responsible AI frameworks covering:
- Bias detection and mitigation
- Explainability
- Model transparency
- Ethical AI adoption
- Audit trail design
- Ensure compliance with corporate, industry, and regulatory AI requirements.
- Lead client architecture workshops and executive design reviews.
- Govern AI-First Application Development Lifecycle (ADLC) adoption across delivery portfolios.
- Define standards for AI-generated code quality, validation, and production readiness.
- Drive reusable AI architecture patterns, accelerators, and playbooks across engagements.
- Design AI-powered decisioning systems for regulated industries.
- Define compliance controls and governance checkpoints for high-risk AI use cases.
- Establish monitoring and observability frameworks for AI-driven business processes.
- Act as a trusted advisor to clients and internal leadership teams.
- Influence AI strategy, architecture standards, and innovation roadmaps.
- Mentor architects, AI engineers, and enterprise technology leaders.
- Contribute to Cognizant's AI intellectual property, frameworks, and industry best practices.
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.
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.










