Data Scientist

• Design and develop generative AI infrastructure, including LLM deployment pipelines, vector databases, APIs, and agent orchestration frameworks — used in real-world GenAI platforms such as OpenClaw

• Build LLM-powered applications such as chatbots, document processing systems, content generation tools, and intelligent assistants

• Design, implement, and maintain retrieval-augmented generation (RAG) pipelines, knowledge bases, and data ingestion workflows

• Apply prompt engineering, fine-tuning, and model selection techniques to optimize performance, cost, and latency

• Deploy, monitor, and evaluate production-grade GenAI solutions using LLMOps best practices (evaluation, prompt versioning, guardrails)

• Ensure security, scalability, reliability, and responsible AI compliance across all AI deployments

• Design and implement AI agents and multi-agent systems for workflow automation and decision support

• Collaborate with business, product, and engineering teams across subsidiaries to identify and deliver AI use cases
• Translate technical AI capabilities into actionable insights for stakeholders and leadership

• Track advancements in generative AI and integrate relevant innovations into business solutions
• Contribute to AI transformation initiatives and internal knowledge-sharing activities

Requirements

• 2–5 years of experience in data science, machine learning, or applied AI, with strong Python skills and hands-on experience in large language models, prompt engineering, and retrieval-augmented generation (RAG)

• Experience with GenAI frameworks, API development, vector databases, and cloud AI platforms is required

• Familiarity with structured and unstructured data, text and document processing, embeddings, AI agents, and standard development tools such as Git/GitHub and Jupyter Notebooks is expected
• Fluency in Azerbaijani and English is required