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Cognizant
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Solution Architect

Solution Architect

Cognizant

18 - 20 years

0 Lacs

bengaluru karnataka india

Posted:5 days ago| Platform: Foundit logo

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Skills Required

sft compliance llmops drift detection model training expertise ai rmf hyperscaler certifications responsible ai practices rag evaluation pipelines lora eu ai act nist enterprise ai ecosystems fine-tuning qlora observability multi-agent orchestration monitoring rlhf

Work Mode

On-site

Job Type

Full Time

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

.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

18+ 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.

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