A leading AI solutions company is looking for an experienced professional to design and oversee complex AI/LLM solutions in cloud and on-premise environments. The ideal candidate will have a strong background in AWS and Python, with at least 5 years of experience in AI projects, including LLM. Responsibilities include consulting for business clients, implementing generative solutions, and leading engineering teams. This position offers flexible working hours with the possibility of remote work, private healthcare, and participation in advanced Data Science projects.
Qualifications
Minimum 5–7 years of experience in implementing AI projects, with 3 years in LLM.
Experience in designing enterprise-level AI/LLM architectures.
Ability to translate complex AI concepts into simple business terms.
Responsibilities
Designing AI solutions in cloud and on-premise environments.
Implementing advanced generative solutions and agent architectures.
Consulting for clients on AI use cases and business cases.
Skills
AWS
Python
AI/ML frameworks
SQL
RAG
Prompt engineering
ETL
Model monitoring
Education
Higher education in computer science, data science, or related fields
Tools
AWS SageMaker
AWS Bedrock
Job description
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 (LangChain, LangGraph, 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
Requirements
Higher education (computer science, data science, mathematics, econometrics, quantitative methods, or related fields)
Very good knowledge of AWS, in particular AWS SageMaker 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 (GitLab/GitHub)
Ability to think analytically and translate complex AI concepts into simple business terms
Very good English (C1)
What we offer
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