Gen AI Architect

Cognizant; Indore District, Hyderabad, Chennai; Hybrid; INR 2.600.000 - 4.200.000; Vollzeit

Zusammenfassung

Cognizant is seeking a Gen AI Architect to design and scale Generative AI solutions across Azure, AWS, and GCP, focusing on cloud-native deployments and containerized apps.

You will mentor AI engineers, establish observability, build MLOps pipelines, and advance multi-agent and RAG architectures, collaborating with product teams in Chennai, Hyderabad, Bengaluru, and Indore.

Qualifikationen

• Experience architecting Gen AI solutions on cloud platforms
• Strong knowledge of ML/DL frameworks and APIs
• Experience in building scalable AI systems and MLOps pipelines
• Familiarity with prompt engineering, vector search, and RAG architectures
• Mentorship of engineering teams in AI best practices

Aufgaben

• Architect and develop scalable, high-performance Generative AI solutions on cloud platforms
• Design, build, and manage containerized AI applications using Docker and orchestrate deployments via Kubernetes
• Establish observability for LLMs including performance monitoring and analytics
• Develop ML models using Python or R with TensorFlow, PyTorch, or scikit-learn
• Build and deploy AI/ML solutions using cloud-native services like SageMaker, Azure AI, Vertex AI
• Design multi-agent systems and RAG architectures
• Lead MLOps pipelines from training to deployment and monitoring
• Collaborate with cross-functional teams to integrate AI into enterprise products
• Lead performance tuning and troubleshooting of AI-driven apps
• Establish secure, scalable, and maintainable AI architectures
• Mentor AI engineering teams on emerging technologies

Kenntnisse

Generative AI

Architectural design

Cloud platforms

Docker

Kubernetes

Python

R

TensorFlow

PyTorch

scikit-learn

MLOps

LLMs

Prompt engineering

Vector search

RAG

SageMaker

Vertex AI

Observability

Tools

Docker

Kubernetes

SageMaker

Vertex AI

Jobbeschreibung

Role: Gen AI Architect

Location: Chennai, Hyderabad, Bengaluru, Indore

• 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