GenAI Architect

Cognizant Technology Solutions Corporation; Chennai, Hyderabad; Hybrid; INR 4,000,000 - 9,000,000; Full time

Job summary

Cognizant Technology Solutions Corporation in Chennai is seeking a pragmatic futurist and technologist to architect and scale Generative and Agentic AI ecosystems for strategic clients in an AI-first era.

This role blends advisory, hands-on solutioning, and leadership to drive AI roadmaps that deliver measurable business outcomes across industries. You will lead cross-functional AI capability practice and collaborate with hyperscalers to co-create offerings.

Qualifications

• 10+ years in IT & architecture
• 5+ years in AI/ML
• Model training expertise: fine-tuning, RLHF, LoRA/QLoRA
• Hyperscaler certifications: AWS/Azure/GCP
• MLOps/LLMOps mastery: CI/CD, observability
• CxO advisory: exec AI strategy discussions
• Governance: AI RMF/NIST, EU AI Act

Responsibilities

• Architect & Implement Enterprise AI Ecosystems: design modular, scalable AI platforms with LLMs/SLMs and multi-agent orchestration.
• Drive AI Strategy: anchor architect for major client accounts and define AI roadmaps linked to business outcomes.
• Industry-specific AI Solutions: envision, design and deliver vertical AI use cases across industries.
• Develop, Train & Optimize Models: end-to-end model lifecycle including data prep, training, fine-tuning, deployment, monitoring.
• MLOps & LLMOps Leadership: establish enterprise standards for pipelines, governance, and auditing.

Skills

IT architecture

AI/ML

Generative AI

MLOps

CxO advisory

Governance

People leadership

Ecosystem influence

Hyperscaler certifications

Business acumen

Tools

AWS

Azure

GCP

Job description

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