Generative AI Lead

Work Experience: 8-12 years

Work Location: Kochi/Bangalore

Work Mode: Hybrid

Must Have Skills: Generative AI, Agentic AI, LLM, RAG, Python

Role Overview

As an AI Architect and Lead you will play a pivotal role in designing, developing, and deploying cutting-edge automation and AI solutions. You will collaborate with cross-functional teams to drive agentification initiatives, leverage the latest advancements in Generative AI, and ensure robust, scalable deployments on leading cloud platforms. This is an exciting opportunity to build your expertise, shape platform-level capabilities, and contribute to impactful, real-world projects.

Key Responsibilities

• Design, build, and enhance automation frameworks using tools such as Selenium and/or Playwright, integrated with cloud-native architectures.
• Lead and support agentification initiatives, including researching and implementing state-of-the-art Generative AI models (LLMs, diffusion models, audio/video models).
• Develop and productionize Retrieval-Augmented Generation (RAG) pipelines to improve the accuracy, grounding, and relevance of AI outputs.
• Implement AI agents and multi-agent systems using frameworks like LangChain, LangGraph, MCP, and other orchestration patterns.
• Apply prompt engineering and system design techniques to optimize model performance across various use cases.
• Prototype AI-driven solutions, demonstrate capabilities through working demos, and iterate based on stakeholder feedback.
• Design and manage scalable deployment pipelines for AI and automation solutions on Azure and/or AWS.
• Evaluate and benchmark AI/ML services across cloud providers for performance, scalability, and cost efficiency.
• Work closely with engineering, product, and business stakeholders to validate solutions and drive adoption.

Core Technical Skills

• Strong proficiency in Python and hands-on development experience.
• Experience building automation solutions using Selenium and/or Playwright.
• Solid understanding of SQL and data handling for analytics or AI workflows.
• Hands-on experience with cloud platforms (preferably Azure; AWS also considered).
• Practical experience with Generative AI, including LLM-based systems.
• Strong understanding of RAG architectures, embeddings, vector databases, and grounding strategies.
• Experience with LangChain, LangGraph, or similar GenAI orchestration frameworks.
• Exposure to AI agents, multi-agent systems, and emerging standards such as MCP.
• Hands-on coding experience with multi-modal AI (speech, transcription, synthesis, or related domains).

Educational Qualification: BTech/BE/ME/MTech/MCA/MSc