AI/ML Technical & Solution Architect

Position- AI/ML Architect

Location- Bangalore (Hydrid)

Exp- 15+ yrs

We are seeking a highly experienced AI/ML Technical & Solution Architect to lead the design, architecture, and implementation of enterprise-scale AI solutions. The ideal candidate will have deep expertise in Artificial Intelligence, Machine Learning, Generative AI, and cloud-native architectures, with a strong background in translating business requirements into scalable, production-grade solutions. This is a hands-on Individual Contributor (IC) role that requires end-to-end ownership, from solution design and model evaluation to deployment, integration, and enterprise adoption

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Key Responsibility-

AI/ML Solution Architect

• Architect and design scalable AI/ML, Generative AI, and Agentic AI solutions for enterprise environment.
• Translate business requirements into technical solutions and define end-to-end architecture pattern.
• Design, evaluate, and optimize AI models for production deployment.
• Build reusable AI frameworks, accelerators, and reference architecture

Generative AI & Agentic

• AI Design and implement GenAI applications using Large Language Models (LLMs
• Build AI agents and multi-agent systems to automate complex business workflow
• Develop Retrieval-Augmented Generation (RAG) solutions using vector databases and knowledge retrieval framework
• Implement prompt engineering, model orchestration, and AI governance framework

Cloud, Data & MLO

• Design AI platforms leveraging cloud technologies (AWS, Azure, GCP
• Build scalable AI pipelines using MLOps and CI/CD methodologies
• Integrate AI solutions with enterprise applications, APIs, and data platform
• Optimize performance, scalability, observability, and cost efficiency of AI system

Mandatory Skills

• 15+ years of IT experience with strong Solution Architecture and technical leadership experien
• Deep expertise in AI/ML algorithms, Deep Learning, NLP, and Computer Vision.
• Hands-on experience with Generative AI, Agentic AI, and Large Language Models (LLM)
• Experience designing and deploying RAG architectures and vector database
• Strong programming skills in Python (mandatory); exposure to R is an advanta
• Hands-on experience with AI/ML frameworks such as TensorFlow, PyTorch, Scikit-learn, LangChain, LangGraph, and MLflow.
• Strong understanding of MLOps, model deployment, monitoring, and AI lifecycle management.
• Experience with cloud platforms (AWS, Azure, GC
• P).Strong understanding of microservices, APIs, distributed systems, and cloud-native architectures.
• Experience with Elastic Search, Kubernetes, Docker, and CI/CD pipelines.
• Excellent analytical, problem-solving, and performance optimization skills.
• Experience building enterprise AI platforms and AI-powered products.
• Exposure to multi-agent systems, AI governance, and responsible AI frameworks.
• Experience integrating AI solutions into existing enterprise ecosystems.
• Background in product engineering, platform engineering, or enterprise modernization.