Generative AI Engineer

As part of our expanding AI and Data capabilities, we are looking for a  Generative AI Engineer with deep technical expertise in Large Language Models (LLMs), Agentic Architectures, and Retrieval-Augmented Generation (RAG) systems. This role will play a key part in designing advanced LLM-driven solutions, building intelligent agentic frameworks, and deploying production-ready GenAI environments for our customers.

Responsibilities

• Design and implement LLM-based Agentic Systems that integrate reasoning, retrieval, and orchestration capabilities
• Develop and optimize RAG architectures (GraphRAG, Agentic Retrieval, Hybrid Indexing) for enterprise-scale use cases
• Build complex agent frameworks using tools such as LangGraph, OpenAI Agent SDK, and LlamaIndex
• Deploy and manage LLM and Embedding inference across Azure Cloud and On-Prem environments (Docker, Kubernetes, VLLM, Triton Inference Engine)
• Define LLM evaluation metrics, establish continuous testing environments, and monitor model quality and performance
• Implement GuardRail and Responsible AI principles to ensure ethical, secure, and transparent AI applications
• Collaborate with AI teams to integrate multimodal models (text, audio, vision) where applicable
• Mentor and support GenAI Engineers, contributing to capability development within the organization

Qualifications

• Bachelor’s or Master’s degree in Computer Engineering, Artificial Intelligence, Data Science, or a related field
• Proven expertise in frameworks such as LangGraph, OpenAI Agent SDK, LlamaIndex, or LangChain
• Hands-on experience building end-to-end RAG systems (GraphRAG, Agentic Retrieval).
• Strong knowledge of Azure AI Services, NVIDIA CUDA / TensorRT / NIM, and AI infrastructure deployment
• Experience with LLM inference deployment in both Cloud and On-Prem environments.
• Understanding of Responsible AI, GuardRail, and AI Safety standards
• Familiarity with LLM evaluation (benchmarks, eval sets, human-in-the-loop frameworks).
• Knowledge of multimodal AI models (text, audio, vision, video)
• Excellent system design, analytical thinking, and problem-solving skills
• Fluent in English (reading, writing, and communication)

 Bonus Qualifications

• Certifications such as Azure AI Engineer Associate, NVIDIA-Certified Associate: AI Infrastructure and Operations, Azure Data Scientist Associate
• Experience in GPU optimization, model quantization, fine-tuning, and distillation
• Proven experience in production-level AI pipeline orchestration and monitoring