AI Engineer (AI Marketing)

AI Engineer at Sber, creating AI products for marketing transformation. Hybrid work, Moscow office.

We create AI products that transform marketing work: from research analysis and client insights to an intelligent copilot helping marketers work with data, documents, content, and creatives. If you are interested not just in connecting LLMs via API, but in understanding how modern AI systems work, designing their architecture, and turning model capabilities into working products, join our team. Tasks: - Develop AI services: from prototype and approach selection to integration into existing technology landscape - Design LLM interaction with tools, data, APIs, and other services - Develop an AI copilot for marketing: work with documents and presentations, content generation, search and information analysis - Research new LLMs, existing frameworks and tools, and determine where they can have practical effect in the product - Design approaches to evaluating AI system quality, conduct experiments, and improve solutions based on results - Participate in designing the architecture of AI products and agentic systems based on modern LLMs.

Higher education. Experience in Python development and industrial AI/ML systems development from 3 years. Deep understanding of modern LLM systems: inference, context management, tool/function calling, structured output, caching, embeddings, RAG, and agentic workflows. Good understanding of system design: architectures of modern applications and services, integration patterns, APIs, queues, storage, caching, and approaches to building systems. Practical experience creating products and services based on LLMs. Experience integrating LLMs into existing systems and working with external and internal APIs. Experience with vector search and databases (Elastic, Chroma, Weaviate or similar). Skills working with LLM serving engines (vLLM, ollama, sglang). Understanding of LLM evaluation approaches and ability to turn subjective 'works well' into measurable quality criteria. Product thinking: ability to work with requirements of varying detail, independently work out solution details, propose implementation options, quickly test hypotheses, and together with product owner find objective quality criteria for AI product. Nice to have: experience creating AI assistants, copilots, or agentic systems for B2B/enterprise scenarios. Experience with LangGraph, LangChain, LlamaFactory, Unsloth or similar tools. Understanding of marketing processes and tasks. Publications, open-source, or personal AI projects.

Hybrid work format, office in Moscow on Kutuzovsky 32. Annual salary review, annual bonus. Corporate gym and relaxation areas. More than 400 educational programs of SberUniversity for professional and career development. Extended voluntary health insurance, preferential insurance for family, and corporate pension program. Flexible discount on mortgage loan equal to 1/3 of the Central Bank's key rate. Prime subscription with possibility of shared use by three close people. Reward for recommending friends to Sber team.