AI Senior Architect

Job Title: Senior AI Architect (GenAI / Agentic AI)

Experience: 10-15 Years (Minimum 5+ Years in AI / Generative AI)

Location: PAN India (Preferred: Pune, Chennai, Hyderabad, Kolkata, NCR, Mumbai)
Employment Type: Full Time

Job Summary

We are seeking a highly experienced Senior AI Architect to lead the design, architecture, and deployment of enterprise-scale Artificial Intelligence and Generative AI solutions. The ideal candidate will have deep expertise in LLMs, Agentic AI, RAG architectures, Multi-Agent Systems, MLOps, GenAIOps, and cloud-native AI platforms across Azure, AWS, and Google Cloud.

This role requires a strong technology leader capable of defining AI strategy, architecting scalable and secure solutions, mentoring engineering teams, and driving AI transformation initiatives across the organization.

Key Responsibilities

AI & GenAI Architecture

• Architect and deploy enterprise-grade AI and Generative AI solutions in production environments.
• Design scalable, secure, resilient, and high-performance AI platforms and applications.
• Define reference architectures, standards, and best practices for AI adoption across the organization.
• Lead the implementation of Large Language Model (LLM)-based solutions and AI-driven business applications.

Agentic AI & Intelligent Systems

• Design and implement Agentic AI systems leveraging autonomous and semi-autonomous agents.
• Architect solutions using Model Context Protocol (MCP), orchestration frameworks, tools, memory management, workflows, and reasoning frameworks.
• Develop multi-agent ecosystems for enterprise automation and intelligent decision-making.

Enterprise AI Solution Design

• Design advanced AI solutions including:

• Retrieval-Augmented Generation (RAG)
• Multi-Agent Systems
• Knowledge Assistants
• Enterprise AI Automation
• Conversational AI Platforms

• Intelligent Business Workflows

• Collaborate with business stakeholders to define and deliver AI-powered transformation initiatives.

Cloud & Platform Architecture

• Design and govern enterprise AI architectures across:

• Microsoft Azure
• Amazon Web Services (AWS)

• Google Cloud Platform (GCP)

• Establish cloud-native AI frameworks that support scalability, governance, security, and operational excellence.

MLOps & GenAIOps

• Define and implement enterprise MLOps and GenAIOps frameworks.

• Drive:

• CI/CD Automation
• Model Versioning
• Experiment Tracking
• Deployment Automation
• Rollback Strategies
• Prompt Lifecycle Management
• Model Evaluation Frameworks
• Automated Retraining Pipelines

AI Operations & Governance

• Establish AI operational processes covering:

• DevOps
• DataOps
• MLOps
• GenAIOps
• Infrastructure Automation
• Observability
• Monitoring

• Governance Frameworks

• Ensure responsible AI implementation and compliance with organizational standards.

Leadership & Stakeholder Management

• Provide technical leadership across the entire AI solution lifecycle.
• Mentor architects, data scientists, AI engineers, and platform teams.
• Collaborate closely with business leaders, Centers of Excellence (CoEs), engineering leadership, and external partners.
• Drive innovation and thought leadership in emerging AI technologies.

Required Skills

AI & Generative AI

• 5+ years of hands-on experience in AI/Generative AI.
• Proven experience in implementing and managing production-grade AI solutions.

• Deep expertise in:

• Generative AI
• Large Language Models (LLMs)
• Agentic AI
• RAG Architectures
• Prompt Engineering
• Multi-Agent Systems

Architecture

• Strong experience architecting enterprise-scale solutions.

• Expertise in:

• Microservices Architecture
• API-Driven Design
• Event-Driven Architecture
• Enterprise Integration Patterns

Cloud Platforms

• Extensive experience with:

• Microsoft Azure
• AWS
• Google Cloud Platform (GCP)

MLOps & GenAIOps

• Strong hands-on experience with:

• CI/CD for AI/ML
• Model Deployment
• Model Lifecycle Management
• Experiment Tracking
• Automated Retraining
• Monitoring & Observability
• Prompt Management Frameworks

AI Operations

• Experience in:

• Model Monitoring
• Drift Detection
• Performance Management
• Incident Management
• Capacity Planning
• Operational Governance

Preferred Skills

• Experience with LangChain, LangGraph, Semantic Kernel, CrewAI, AutoGen, or similar orchestration frameworks.
• Experience with Vector Databases such as Pinecone, Weaviate, Milvus, Chroma, or Azure…