Role: Gen AI & Agentic AI Architect

Location : Pan India

Experience : 6 to 15 Years

Notice Period : Immediate to 90 days

Mode of Interview : In Person

Gen AI & Agentic AI Architect

About The Role

We are seeking a highly experienced GenAI & Agentic AI Architect with strong hands-on expertise to lead the design, development, and implementation of advanced AI solutions for our clients. This role requires a seasoned technical leader with over 8 years of architecture experience and deep knowledge of Azure and/or AWS cloud ecosystems, combined with strong capabilities in containerization, orchestration, observability, and modern AI frameworks.

You will play a critical role in shaping next-generation AI systems, leveraging Generative AI and Agentic AI paradigms to build scalable, intelligent, and action-oriented solutions.

Key Responsibilities

Architect and develop scalable, high-performance Generative AI solutions on Azure and/or AWS 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

Required Skills & Qualifications

Minimum 8+ years of experience in a technical architecture role
Proven expertise in Azure and/or AWS cloud architectures
Strong hands-on experience with Docker and Kubernetes
Proficiency in Python or R with experience in TensorFlow, PyTorch, or scikit-learn
Deep knowledge of MLOps practices and model deployment on AWS SageMaker, Azure AI, or Google Vertex AI
Experience with multi-agent orchestration and RAG architectures
Solid understanding of prompt engineering, vector search, and LLM observability frameworks
Experience with Spring Boot and microservices architecture
Strong understanding of enterprise AI security, scalability, and governance principles