Job Description

As a Data Scientist you will:

Build intelligent, end-to-end data pipelines that utilize large language models (LLMs) for document generation, summarization, reasoning, and automating tasks.


Design and develop autonomous workflows where AI agents interact with tools, APIs, memory, and other agents to accomplish complex, multi-step objectives.


Apply prompt engineering, retrieval-augmented generation (RAG), and planning techniques to enable contextual reasoning and decision-making in LLM-powered systems.


Analyze legacy systems such as rule-based engines, stored procedures, and monolithic applications, and convert them into modular, AI-native components that work with structured and unstructured data.


Fine-tune foundation models or adapt them using low-rank adaptation (LoRA), transfer learning, or domain-specific techniques for enhanced task performance.

Skills Required

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5+ years of experience in AI/ML development, with a strong emphasis on LLM integration and intelligent system design. Proven experience in designing, developing and deploying real-world LLM-based applications and agentic systems. Expert-level knowledge of Python for building and orchestrating machine learning and AI applications, with a focus on LLM-based development. Proficiency in prompt engineering, chaining logic, context window management, and invoking tools (e.g., APIs, functions) within LLM applications. Understanding of agent patterns involving memory, planning, multi-agent coordination, and decision-making frameworks. Experience with vector databases, embedding generation, and retrieval-augmented generation (RAG) for knowledge-based AI systems. * Hands-on experience deploying and managing AI services in cloud platforms, preferably Microsoft Azure.