AI Backend Developer at Yandex KIT

Yandex KIT is a new technology platform for launching and developing independent e-commerce. We are building the platform and integrating artificial intelligence into its key components.

The first major step is the creation of AI Support, a smart assistant for sellers. It will help manage the store, work with analytics, discounts, orders, and platform tools.

You will have the opportunity to be at the origins of the AI direction in a new, fast-growing product. We offer freedom of decision-making, a high level of responsibility, access to the latest models and tools, as well as the support of an R&D team.

What tasks await you

Designing architecture and business logic You will participate in creating scalable AI infrastructure, develop the backend logic of the assistant, APIs, integrations, and microservices. You will also need to consider latency, fault tolerance, and load issues.

LLM Integration You will need to integrate a modern LLM model via API, experiment with different versions, and configure the model for specialized agents.

MCP Development You will participate in the creation and development of the MCP platform.

Development and Implementation of RAG System You will develop and scale a RAG system, including configuring indexes, organizing knowledge storage, and ensuring effective search. It will also be necessary to implement RAG, build pipelines for information preparation, and optimize text2vec models to improve candidate selection.

Collaboration with Related Teams You will collaborate with ML engineers, product specialists, and a dialogue designer.

We expect you to

• Are proficient in Go or Python
• Can independently research, propose, and implement engineering solutions
• Want to be not just an executor, but a co-author of the architecture and product

It will be a plus

• Have developed with LLMs in production
• Have worked with LangChain, CrewAI, and similar frameworks
• Have participated in the creation of assistants, bots, voice or chat interfaces
• Understand microservice architecture and API integrations
• Understand prompt engineering and orchestration of model calls