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Gen AI

Cognizant

Chennai

8-15 years

Today

$43.4K–68.7K/yr

Full-time

Hybrid

Skills Required LLM

RAG

Gen AI

Agentic AI

Prompt Engineering

LLM observability

Vector search

Azure

AWS

Docker

Kubernetes

Python

R

TensorFlow

PyTorch

Description Cognizant is seeking a highly experienced GenAI and Agentic AI Architect to lead the design, development, and implementation of advanced AI solutions for clients. The role focuses on building scalable, intelligent, action-oriented systems across cloud and contemporary AI platforms.

Company: Cognizant

Role: Gen AI & Agentic AI Architect

Location: Chennai / India | Pan India | Hybrid

Experience

- 6 to 15 years
- Minimum 8+ years of experience in a technical architecture role
- Over 8 years of architecture experience
- Mode of Interview: In Person

Responsibilities

- Lead the design, development, and implementation of advanced AI solutions
- Architect and develop scalable, high-performance Generative AI solutions on Azure and/or AWS
- Design, build, and manage containerized AI applications
- Orchestrate deployments via Kubernetes
- Establish and maintain observability frameworks for LLMs
- Develop and implement machine learning models
- Build and deploy AI/ML solutions using cloud-native services
- Design and implement multi-agent systems and RAG architectures
- Define and enforce standards for prompt engineering, vector search, and model orchestration
- Build and manage enterprise-grade MLOps pipelines
- Collaborate with cross-functional teams to integrate AI capabilities into enterprise products and platforms




- Lead system optimization, performance tuning, and troubleshooting of AI-driven applications
- Establish best practices for secure, scalable, and maintainable AI architectures
- Mentor and guide AI engineering teams
- Stay current with advancements in Generative AI, Agentic AI, and cloud technologies

Additional Responsibilities

- Monitor system health and usage analytics for LLMs
- Cover model training, fine-tuning, evaluation, deployment, and monitoring in MLOps pipelines

More Skills Observability, scikit-learn, AWS SageMaker, Azure AI, Google Vertex AI, Multi-agent systems, Retrieval-Augmented Generation (RAG), Model orchestration, MLOps, Spring Boot, Microservices architecture, Enterprise AI security, Scalability, Governance, LLM observability frameworks

Prepare for this role

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Top 50 Multi-Agent Systems Interview Questions

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