AI Engineer

The AI Engineer role demands more than AI-based augmentation with an in-depth understanding of concepts like RAG-GenAI, LLM finetuning, prompt engineering, multi-agent frameworks (LangChain, LangGraph, etc. with hands-on experience), eval generation and its importance, and token usage and optimizations.

Requirements:

• Strong software engineering in Python (and one of Node/Java/Go), REST/gRPC APIs, queues, and microservices on cloud infrastructure.
• Hands-on experience shipping at least one AI-powered product to production (e. g., search, recommendations, chatbots, summarization, classification).
• Practical knowledge of LLM concepts: prompts, context engineering, embeddings, vector search, basic evaluation metrics, and latency/cost trade-offs.
• Solid understanding of integration patterns with third-party AI providers (OpenAI, Anthropic, etc. ) and vector DB.
• Hands-on and good understanding of at least one agentic framework like LangGraph.