AI Engineer (LLM / GenAI)

Key Responsibilities: Solution Architecture & Deployment: Design and deploy secure, scalable GenAI architectures integrated into applications Build and deploy REST APIs for AI/ML models Work with Docker, Kubernetes in cloud environments (AWS/Azure/GCP) GenAI & LLM Development: Fine-tune and optimize LLMs (GPT, VAEs, GANs, transformer-based models) Implement RAG pipelines, embedding, and prompt engineering techniques Work with commercial and open-source LLMs (GPT, Claude, LLaMA, Phi) Agentic AI Development: Build and deploy AI agents using LangChain, LangGraph, CrewAI, Autogen, AgentFlow Implement multi-agent systems, orchestration, tool integration, and state management Develop autonomous or semi-autonomous workflows for business use cases MLOps & Optimization: Set up end-to-end MLOps pipelines (CI/CD, monitoring, retraining) Optimize performance, scalability, and infrastructure costs Use tools like Git, Docker, Kubernetes, vector databases Application Development & Data Integration: D...