Consulting Principal, Enterprise AI

About Cognizant Consulting

Cognizant Consulting is more than Cognizant’s consulting practice—we’re a global community of 5,000+ experts dedicated to helping clients reimagine their business. Blending our deep industry and technology advisory capability, we create innovative business solutions for Fortune 500 clients.

About the role

As a Consulting Principal, Enterprise AI you will make an impact by defining enterprise-wide AI architecture strategy and establishing scalable, secure, and governed AI solutions across a portfolio of SaaS, fintech, payments, and Hi-Tech clients. You will be a valued member of the Enterprise Architecture team and work collaboratively with executive stakeholders, solution architects, engineering leaders, product teams, delivery organizations, and client leadership to drive AI transformation at enterprise scale.

Responsibilities

• Define enterprise AI architecture vision, governance standards, and target-state roadmaps that enable AI-augmented operations, intelligent automation, and enhanced customer and employee experiences
• Architect scalable, resilient, explainable, and secure GenAI, machine learning, RAG, and agentic AI solutions while establishing reusable reference architectures and accelerators across client portfolios
• Design cloud-native architectures and integration patterns across AWS, Azure, and GCP, ensuring AI capabilities are seamlessly integrated with SaaS platforms, payment ecosystems, finance systems, ServiceNow, Salesforce, DocuSign, and other enterprise applications
• Establish architecture governance, responsible AI standards, model evaluation frameworks, compliance controls, and Architecture Review Board processes to ensure production-ready solutions
• Serve as a trusted advisor to client executives while supporting solutioning, pre-sales activities, discovery workshops, proof-of-concepts, and large-scale transformation initiatives

Work model

Hybrid position requiring 3 days a week in a client or Cognizant office. Working arrangements are accurate as of the date of posting and may change based on project, business, and client requirements.

Requirements

• 12–15+ years of Enterprise Architecture experience supporting large-scale enterprise technology transformation programs
• Proven experience architecting enterprise-grade AI, GenAI, machine learning, and agentic AI solutions
• Deep expertise with TOGAF Architecture Development Method (ADM) and Enterprise Architecture governance frameworks
• Significant client-facing consulting experience, including executive stakeholder engagement, solutioning, pre-sales, and strategic advisory responsibilities
• Strong experience designing cloud-native architectures across AWS, Azure, and/or Google Cloud Platform
• Expertise in microservices, Kubernetes, Docker, event-driven architecture, Kafka, REST APIs, and enterprise integration patterns
• Experience designing GenAI solutions including RAG architectures, vector databases, LLM onboarding, AI orchestration frameworks, and autonomous agent solutions
• Strong understanding of AI governance, responsible AI practices, model evaluation frameworks, privacy requirements, and regulatory compliance controls
• Demonstrated ability to independently develop proofs of concept and working prototypes to validate AI solutions and architecture decisions
• Experience establishing architecture standards, reusable frameworks, governance processes, and enterprise reference architectures

Preferred qualifications

• Domain expertise in SaaS platforms, fintech and payments, finance automation, semiconductor manufacturing, or Hi-Tech enterprise environments
• Experience supporting fraud detection, risk decisioning, payment processing, ledger platforms, identity management, compliance, and financial automation initiatives
• Experience integrating AI solutions with Salesforce, ServiceNow, DocuSign, ERP platforms, finance systems, and payment ecosystems
• Hands-on experience with LangChain, LlamaIndex, MLflow, Hugging Face, PyTorch, TensorFlow, and vector database technologies
• Experience designing enterprise data platforms, lakehouse architectures, Kafka-based streaming solutions, and large-scale analytics ecosystems
• Experience operating within highly regulated environments requiring PCI-DSS, SOX, privacy, fraud prevention, resilience, and audit controls
• Experience leading Architecture Review Boards, Design Review Boards, and enterprise governance councils
• Experience developing proposals, estimates, statements of work, and executive-level solution presentations
• TOGAF certification and cloud architecture certifications across AWS, Azure, or GCP