Lead AWS AI Engineer

Responsibilities

• Design and architectural oversight of complex AI/LLM solutions in cloud and on-premise environments
• Building and implementing advanced generative solutions (GenAI), including RAG (Retrieval-Augmented Generation) systems, agent architectures and agent orchestration (Lang Chain, Lang Graph, Haystack, Semantic Kernel), multimodal solutions (text, image, sound, video)
• Designing and managing end-to-end projects – from analysis and PoC to production implementation
• Consulting and advising for business clients – identifying AI use cases, creating business cases, evaluating business value
• Conducting evaluations of new AI/LLM technologies (open-source and commercial, including Hugging Face, OpenAI, Anthropic, Meta, Mistral, Google, Cohere)
• Implementation and optimization of MLOps/LLMOps processes (model monitoring, retraining automation, champion‑challenger)
• Substantive leadership of engineering teams implementing AI solutions, mentoring, and support in technological decision‑making

• Higher education (computer science, data science, mathematics, econometrics, quantitative methods, or related fields)
• Very good knowledge of AWS, in particular AWS Sage Maker and Bedrock
• Minimum 5–7 years of experience in implementing AI projects, including at least 3 years of LLM experience
• Experience in designing the architecture of enterprise‑level AI/LLM solutions
• Proficient Python skills and practical experience with AI/ML frameworks
• In‑depth knowledge of RAG, prompt engineering, fine‑tuning and adapters (LoRA, PEFT), training and evaluating language models (NLP, LLM, multimodal), agent orchestration, and AI workflows
• Experience in data preparation for AI solutions (ETL, SQL, data pipelines, embeddings, text and multimodal data cleansing)
• Ability to select appropriate LLM models for specific tasks based on benchmarks, quality metrics, costs, and business requirements
• Knowledge of engineering best practices: CI/CD, code review, testing (Git Lab/Git Hub)
• Ability to think analytically and translate complex AI concepts into simple business terms
• Very good English (C1)

• Participation in diverse and technologically advanced Data Science and GenAI projects
• Modern technology stack and openness to implementing new solutions
• Work in a Data Science/AI competency team
• Private healthcare and sports card
• Flexible working hours and the possibility of 100% remote work
• Team‑building events and unforgettable company events