Job Description :

We are seeking an AI, Generative AI & Agentic AI Tech Lead/Architect with expertise in designing scalable, high-performance AI and GenAI solutions leveraging agentic frameworks and modern data architectures. The ideal candidate should have deep experience in AI/ML, LLM models, and AI Ops, along with hands-on knowledge and experience of working with at-least one of the hyperscaler cloud platforms (Azure or GCP)

This role requires a strategic thinker who can architect, evaluate, develop and deploy AI/Gen-AI driven solutions, incorporating agentic framework for automation, orchestration, and intelligent decision-making. If you thrive at the intersection of cutting-edge AI/Gen-AI technology, automation, and enterprise-scale data architectures, we want you on our team!

Key Responsibilities :

1. AI, Generative AI & Agentic AI Solution Architecture :

- Design, implement, develop and deploy AI/GenAI solutions using state-of-the-art LLM models (Open AI, llama, Gemini, Mistral, etc.)

- Leverage agentic frameworks like LangChain, LangGraph, Google ADK/Databricks Agentbricks/Azure for automated AI workflows and intelligent decision-making in AI pipelines

- Architect AI-powered retrieval-augmented generation (RAG), multi-agent orchestration, and adaptive learning systems

2. Experience in setting up MLOps, LLMOps & AgenticOps :

- Design scalable data architectures to support AI-driven workloads (Lakehouse, Data Mesh, Feature Stores)

- Ensure efficient vector database integration (e.g., FAISS, Chroma etc.)

- Knowledge of Agent Lifecycle management incl. security, multi agent collaboration, reasoning etc.

3. AI Deployment & Cost Optimization :

- Deploy AI solutions across cloud platforms (AWS, Azure, GCP) with optimal cost-performance balance

- Evaluate LLM cost modeling strategies, ensuring scalable, cost-efficient AI workloads

- Optimize AI infrastructure using serverless architectures, GPUs/TPUs, and distributed model training

4. AI Tooling & Tech Stack Selection :

- Compare, evaluate, and recommend AI tools, frameworks, and cloud-based AI services

- Stay ahead of AI trends, selecting the best LLM fine-tuning techniques (LoRA, PEFT, RLHF)

- Implement multi-modal AI solutions combining text, vision, and speech models

5. AI Governance, Security & Compliance :

- Ensure AI solutions align with ethical AI principles, model interpretability, and responsible AI practices

- Implement AI security measures to protect against model leakage, data poisoning, and adversarial attacks

- Work with stakeholders to establish AI governance framework