Location : Chennai/Hyderabad/Bangalore/Kolkata.

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) .

Valuable 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

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 hy

📌 Enterprise Architect (Bengaluru)
🏢 Cognizant Technology Solutions India
📍 Bengaluru