Sr. Gen AI Architect

Cognizant; Ernakulam, Dadri, Coimbatore District; Hybrid; INR 2,500,000 - 4,500,000; Full time

Job summary

Cognizant is seeking a Sr. Gen AI Architect to lead the design and delivery of scalable, high-performance GenAI solutions across cloud platforms. You will architect multi-domain AI systems, establish MLOps pipelines, and mentor teams on emerging AI technologies.

Primary focus includes building containerized AI apps with Docker/Kubernetes, leveraging cloud services such as AWS/Azure/GCP, and advancing Retrieval-Augmented Generation and prompt engineering within enterprise products.

Qualifications

• Experience architecting Generative AI solutions at scale.
• Proficient in Python or R for ML model development.
• Hands-on with cloud-native AI services (SageMaker/Azure/AWS).
• Familiarity with MLOps pipelines and model deployment.

Responsibilities

• Architect and develop scalable, high-performance Generative AI solutions on cloud platforms.
• Design, build, and manage containerized AI applications using Docker and Kubernetes.
• Establish observability, monitoring, and analytics for LLM deployments.
• Develop ML models using Python or R with TensorFlow, PyTorch, or scikit-learn.
• Lead MLOps pipelines for training, evaluation, deployment, and monitoring.

Skills

Generative AI

Docker

Kubernetes

Python

R

ML frameworks

MLOps

Prompt engineering

Vector search

Tools

SageMaker

Vertex AI

Azure AI

Job description

Role: Sr. Gen AI Architect

Location: PAN India

• Architect and develop scalable, high-performance Generative AI solutions on Azure/AWS/ GCP platforms
• Design, build, and manage containerized AI applications using Docker and orchestrate deployments via Kubernetes
• Establish and maintain observability frameworks for LLMs, including performance monitoring, system health, and usage analytics
• Develop and implement machine learning models using Python or R, leveraging frameworks such as TensorFlow, PyTorch, or scikit-learn
• Build and deploy AI/ML solutions using cloud-native services such as AWS SageMaker, Azure AI, or Google Vertex AI
• Design and implement multi-agent systems and Retrieval-Augmented Generation (RAG) architectures
• Define and enforce standards for prompt engineering, vector search, and model orchestration
• Build and manage enterprise-grade MLOps pipelines covering model training, fine-tuning, evaluation, deployment, and monitoring
• 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 on emerging technologies and implementation best practices
• Stay current with advancements in Generative AI, Agentic AI, and cloud technologies