About the project:

We are building a corporate AI Assistant powered by Microsoft Azure and OpenAI technologies. The system helps employees search, analyze, and generate internal documents. The long-term goal is to extend AI Assistant capabilities across all company departments.

To strengthen our team, we are looking for an experienced ML Architect (Azure AI / RAG) who will design and implement the machine learning architecture, integrate AI models, and ensure production-level performance and reliability.

Responsibilities:

• Design and implement AI architecture on Microsoft Azure (Azure ML, Cognitive Search, OpenAI, Databricks).
• Build and manage RAG pipelines (Retrieval-Augmented Generation) and vector search systems.
• Develop and optimize ML pipelines for embeddings, data preprocessing, and model evaluation.
• Collaborate with DevOps and Data Engineer teams to ensure seamless integration and deployment.
• Establish and maintain MLOps practices (model versioning, evaluation, monitoring).
• Define and track AI performance metrics (latency, precision, recall, cost per request).
• Create documentation (ADR, architecture diagrams, experiment tracking).

Requirements:

• 3+ years of experience in Machine Learning / AI / Data Engineering.
• Strong background with Microsoft Azure ML / Cognitive Search / Databricks / OpenAI.
• Proficiency in Python, FastAPI, LangChain / LlamaIndex, MLflow, Airflow.
• Hands-on experience with vector databases (FAISS, Pinecone, pgvector, Cognitive Search).
• Understanding of RAG, embeddings, prompt optimization, LLM orchestration.
• Experience building MLOps / CI-CD for ML models in production.
• English — Upper-Intermediate+ (for documentation and collaboration).

Will be a plus:

• Experience with Azure OpenAI Service, Azure Document Intelligence.
• Knowledge of data governance, PII protection, cost optimization.
• Background in AI-driven enterprise automation or corporate assistants.

We offer:

• Opportunity to design a core AI architecture from scratch and influence all key technical decisions.
• Participation in a high-impact AI transformation project that scales across multiple departments.
• Remote or hybrid work format, flexible schedule.
• Transparent B2B / contract cooperation.
• Supportive and technically strong team (DevOps, Data, Product).

How to apply:

Send your CV.
We will contact you shortly.