Generative AI Architect

Hi, We have the following role open in Bangalore, Interested candidates can send their detailed profile to mentioning their Current CTC, Expected CTC and Notice period to join.

JD : Gen AI Architect role :

Job Description

We are seeking a visionary and hands-on Generative AI Architect to lead the design, development, and deployment of cutting-edge AI solutions that leverage Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and vector databases. This pivotal role involves defining the enterprise-wide architecture for GenAI systems, ensuring they are scalable, secure, and aligned with business objectives. The ideal candidate will combine deep technical expertise with strategic leadership to drive innovation and integrate AI capabilities into our core products and services.

Key Responsibilities

• AI Architecture & Strategy : Define and evolve the enterprise architecture blueprint for GenAI and agentic systems, creating modular, reusable, and scalable design patterns.
• LLM & Model Selection : Evaluate and select appropriate AI models (e.g., OpenAI's GPT models, open-source models like Llama, Mistral) based on performance, cost, latency, and compliance requirements.
• RAG System Design : Architect and implement end-to-end RAG frameworks for enterprise use cases, combining vector databases, embedding models, and document stores to enhance model accuracy and contextual relevance.
• Prompt Engineering : Develop and optimize advanced prompt engineering strategies, including dynamic templates and multi-turn dialogue strategies, to improve model reliability and control outputs.
• Development & Integration : Build scalable AI pipelines and inference architectures using Python and relevant frameworks ( LangChain , LlamaIndex, PyTorch, TensorFlow). Integrate AI models with enterprise systems via APIs and microservices architectures.
• MLOps / LLMOps : Implement robust MLOps / LLMOps practices for the AI model lifecycle, including CI / CD pipelines, model versioning, performance monitoring, and drift detection.
• Prototyping & PoCs : Rapidly develop Proofs of Concept (PoCs) and pilot initiatives to demonstrate solution feasibility and business value.
• Governance & Ethics : Define AI governance frameworks and ensure all solutions adhere to ethical AI practices, data privacy, and regulatory requirements.
• Collaboration & Mentorship : Partner with data scientists, ML engineers, software developers, and business stakeholders. Provide technical direction and mentorship to cross-functional teams.

Required Qualifications & Skills