A Generative AI (GenAI)
Engineer builds and deploys production-grade applications using large language models and multimodal systems. Specialists bridge frontier AI capabilities with enterprise software by implementing RAG pipelines, agentic workflows, and cloud-based deployments

Key Responsibilities
Model Integration: Connect software with foundation models like GPT, Claude, Gemini, and Llama via APIs.
RAG Pipelines: Build Retrieval-Augmented Generation systems using vector databases.
Agentic Frameworks: Develop autonomous multi-step AI agents via frameworks like LangChain or LlamaIndex.
Fine-Tuning: Adapt and evaluate models for custom enterprise datasets.
Optimization: Monitor inference latency, output accuracy, and token costs. [1, 2, 3, 4, 5]

Required Qualifications & Skills
Programming: Advanced Python proficiency and experience with AI libraries (PyTorch, TensorFlow).
Frameworks: Hands-on skill with LangChain, LlamaIndex, and embedding models.
Cloud Platforms: Deployment experience on AWS, Azure, or Google Cloud.
Background: Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field

📌 Gen Ai London
🏢 Dev-Test- India
📍 London