Senior Data Scientist with NLP

About this role

You’ll be working on diverse machine learning projects for local and international companies as well as in academic research. This will involve different phases of the end-to-end delivery – direct contact with the client, business analysis of the problem, coming up with an appropriate solution, implementation and moving it to the production environment. Requirements Key Responsibilities ● Design and develop end-to-end agentic AI solutions using modern LLM frameworks ● Build and deploy Generative AI applications using Python ● Develop and manage AI agents, including tool integrations, memory management, and reasoning workflows ● Implement agent orchestration for multi-agent systems and complex task automation ● Apply advanced prompt engineering techniques to optimize model performance ● Establish agent observability frameworks (monitoring, tracing, logging, evaluation, guardrails) ● Deploy AI solutions using container-based architectures (Docker, Kubernetes) ● Ensure scalability, reliability, and security of AI systems in production ● Integrate AI agents with enterprise APIs, databases, and external systems ● Continuously evaluate model performance and implement optimization strategies Required Skills & Qualifications: ● Strong proficiency in Python programming ● Hands-on experience with Generative AI / LLM frameworks (e.g., LangChain, LlamaIndex, Semantic Kernel, etc.) ● Experience building end-to-end agentic solutions ● Practical experience in agent development and orchestration ● Expertise in prompt engineering and LLM optimization ● Experience with container-based deployments (Docker, Kubernetes) ● Experience implementing agent observability (monitoring, tracing, evaluation frameworks) ● Knowledge of REST APIs and backend integration patterns ● Experience deploying AI applications in cloud environments (AWS / Azure / GCP) ● Understanding of RAG architectures, embeddings, vector databases Preferred Qualifications: ● Experience with multi-agent collaboration frameworks ● Experience with evaluation tools (e.g., prompt testing, hallucination detection, guardrails) ● Familiarity with MLOps practices ● Knowledge of distributed systems design ● Experience with real-time AI applications ● Background in machine learning fundamentals ● Communicative English – minimum C1 level It is great if you have: Experience with DevOps / MLOps tools and practices (e.g.