Generative AI Architect

Architecting the Future: Agentic AI & Enterprise Transformation: Join us in shaping the next wave of enterprise innovation through Generative and Agentic AI. We are seeking a pragmatic futurist and business-savvy technologist to redefine how enterprises operate in the AI-first era . This strategic role is available across Cognizant’s key delivery locations in India . You will lead the design, adoption, and scaling of Generative and Agentic AI ecosystems for our most strategic clients. This role blends advisory, hands-on solutioning, and practice-building leadership to ensure AI delivers tangible, industry-specific business outcomes . Core Responsibilities Architect & Implement Enterprise AI Ecosystems :Design and implement modular, scalable AI platforms that integrate Large Language Models (LLMs), Small Language Models (SLMs), and multi-agent orchestration . Ensure architectures are cloud-native, secure, and industry-compliant . Drive AI Strategy :Serve as the anchor architect for major client accounts. Lead C-level discussions to define AI roadmaps that link technology to measurable business outcomes. Influence long-term investment strategies. Industry-Specific AI Solutions : Envision, Design and Deliver verticalized AI use cases across one or more industries, including Banking & Financial Services, Consumer Goods, Energy & Utilities, Healthcare, Insurance, Life Sciences, Logistics, Manufacturing, Media, Retail, Telecom, and Travel & Hospitality. Develop, Train & Optimize Models :Lead end-to-end model lifecycle : data preparation, training, fine-tuning , deployment, monitoring, and continuous improvement. Balance LLM vs. SLM adoption for cost, latency, and performance optimization. MLOps & LLMOps Leadership :Establish enterprise standards for MLOps/LLMOps pipelines (CI/CD, monitoring, observability, drift detection, compliance). Build agent lifecycle governance frameworks for scalable, auditable AI systems. People Leadership & Practice Building :Mentor and grow a community of architects and engineers . Build capability squads in GenAI/Agentic AI. Shape the company’s AI practice , including skills development, hiring strategy, and succession planning . Ecosystem & Partner Engagement :Build and leverage strategic partnerships with hyperscalers (AWS, Azure, GCP), ISVs, and AI startups. Co-develop joint offerings, influence partner roadmaps, and co-sell AI solutions into strategic accounts. Innovation & Thought Leadership :Publish white papers, frameworks, and patents . Lead executive roundtables and contribute to the Tech Radar , ensuring the firm shapes the AI conversation in the market. Required Skills & Experience 10+ years in IT & architecture , with clear progression from hands-on engineering (Java/.NET preferred) into enterprise architecture leadership. 5+ years in AI/ML , with 1+ year in Generative & Agentic AI (LLMs, SLMs, multi-agent orchestration). Model Training Expertise : Fine-tuning (SFT, RLHF, LoRA/QLoRA), RAG, evaluation pipelines. Hyperscaler Certifications : Architect-level expertise in at least two (AWS, Azure, GCP). MLOps/LLMOps Mastery : CI/CD pipelines, monitoring, observability, compliance, AI cost governance. CxO Advisory : Proven experience leading executive AI strategy discussions with Fortune 500 clients. Governance Expertise : Familiar with AI RMF (NIST), EU AI Act, Responsible AI practices . People Leadership : Experience mentoring teams and building cross-functional AI capability practices . Ecosystem Influence : Track record shaping AI initiatives through partner alliances (hyperscalers, startups, ISVs) . Good to have. Publications, patents , or open-source contributions in Agentic AI, LLMOps, or model compression/distillation . Recognized thought leadership (conferences, panels, media interviews). Industry domain depth in at least one vertical: Banking & Payments, Consumer Goods, Energy & Utilities, Healthcare, Insurance, Life Science, Logistics, Manufacturing, Media, Retail, Telecom, Travel & Hospitality Experience with AgentOps, model evaluation frameworks, and AI observability tooling . Functional Competencies Business Acumen : Identify and execute high-value AI transformations across industries. Consultative Mindset : Convert PoCs/PoVs into long-term transformation programs . Practice Builder : Mentor, hire, and scale AI architecture talent pools . Ecosystem Shaper : Drive co-innovation with hyperscalers, startups, and ISVs. Pragmatic Execution : Balance build-vs-buy , deliver under pressure, and navigate enterprise politics. Translation & Storytelling : Distill complex AI concepts into clear executive-ready narratives