Role & Responsibilities
Design and define enterprise AI, Generative AI, and Agentic AI solution architectures.
Architect and implement end-to-end AI solutions using Large Language Models (LLMs), RAG, and semantic search.
Develop AI applications using frameworks such as LangChain, LangGraph, or Semantic Kernel.
Design and implement enterprise knowledge management solutions using vector databases and document repositories.
Build scalable, secure, and cloud-native AI solutions on Microsoft Azure.
Collaborate with business stakeholders, data engineers, developers, and cloud teams to deliver production-ready AI solutions.
Establish AI architecture best practices, including MLOps, LLMOps, governance, security, and Responsible AI.
Integrate AI solutions with enterprise applications, APIs, databases, and cloud services.
Provide technical leadership, architecture guidance, and code reviews throughout the project lifecycle.
Ensure AI solutions meet enterprise standards for performance, scalability, security, and compliance.

Preferred Candidate Profile




8+ years of experience in Solution Architecture, Software Engineering, Cloud Architecture, AI/ML, or Data Engineering.
Hands-on experience delivering enterprise Generative AI solutions using LLMs.
Solid expertise in RAG, Agentic AI, semantic search, and enterprise knowledge management.
Experience with AI frameworks such as LangChain, LangGraph, or Semantic Kernel.
Robust knowledge of Microsoft Azure services, including Azure OpenAI and Azure AI Search.
Experience with vector databases such as Pinecone, Weaviate, Milvus, or Azure AI Search.
Strong programming skills in Python and experience developing REST APIs.
Positive understanding of AI governance, Responsible AI, data privacy, and enterprise security.
Experience working with distributed systems, microservices, and cloud-native architectures.
Excellent communication, stakeholder management, and problem-solving skills.

📌 Ai Solution Architect Bengaluru
🏢 Sunovaa Tech
📍 Bengaluru