Location
Remote work

Offer description

We're looking for an AI Expert/LLM to join our team to support the development of innovative solutions based on artificial intelligence and the latest language models. We're looking for someone with extensive technical and architectural knowledge, able to combine engineering skills with experience implementing AI solutions in both cloud and on-premises environments.

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 systems (Retrieval-Augmented Generation), 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 implementation in a production environment
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
Databases and search: Pinecone, Weaviate, FAISS, ElasticSearch

Requirements

Higher education (computer science, data science, mathematics, econometrics, quantitative methods, or related)
Minimum 5–7 years of experience in implementing and implementing AI projects, including at least 3 years of experience with LLM.
Experience in designing the architecture of AI/LLM solutions at the enterprise level.
Proficient knowledge of Python and practical experience with AI/ML frameworks.
In-depth knowledge of: RAG, prompt engineering, fine-tuning, and adapters (LoRA, PEFT), language model training and evaluation (NLP, LLM, multimodal), agent orchestration and AI workflow
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 explain complex AI concepts in a simple way for business.
Very good command of English. (C1)

Technology Stack

Public clouds: core stack - Azure (OpenAI, AI Search, Document Intelligence, Databricks, Azure ML, Databricks) Additionally - AWS (SageMaker, Bedrock), GCP (Vertex AI)
On-prem and open-source: Kubernetes, MLflow, Hugging Face, LangChain, LangGraph, Haystack
ML/DL frameworks: PyTorch, TensorFlow
Orchestration and monitoring: Airflow, Weights & Biases
Frontend prototyping: Streamlit, Gradio
Databases and search: Pinecone, Weaviate, FAISS, ElasticSearch, Snowflake

Welcome

AI/ML Certifications (Azure AI Engineer Associate, AWS Certified Machine Learning – Specialty, Google Cloud ML Engineer, TensorFlow Developer, etc.)
Experience in developing large-scale AI solutions (multi-user production systems)
Experience integrating AI with existing business systems (CRM, ERP, workflow automation)
Experience in an advisory or consulting role

What we offer

Participation in diverse and technologically advanced Data Science and GenAI projects
Modern technology stack and openness to implementing new solutions
Working 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

AI/LLM Expert