Description
Corporate and Investment Division, Corporate Business Development Department.
The Department is responsible for developing sales in the B2B segment: large, major, and medium-sized businesses (LMCB), and developing its own CRM system.
The AI Team consists of 8 ML engineers, Data Scientists, Python backend developers, and MLOps.
Our AI team develops AI Agents, ML models, and LLM applications for corporate business within the Corporate and Investment Division, handling the entire work cycle: from data collection and analysis to model development/deployment to PROD, monitoring, and defending solutions from Banking Regulators.
The product team you will be working in is engaged in the development and implementation of AI solutions aimed at agentifying the process of digital transformation of client business in Sber (DTaaS direction). These tools are designed to optimize and improve the work of our internal employees.
In particular, we:
- develop and implement AI agents based on LLM (typically the SberDevice model line - GigaChat)
- use a modern stack: A2A, MCP, LangGraph, LangChain, Kubernetes, Hadoop, Elastic, and much more
- implement AI Agent orchestration, multi-agent multimodal systems, RAG services
- participate in projects for inference of open-source LLMs on our own GPU cluster, development of a NoCode Agent factory
- develop our own AutoML framework in collaboration with Sber AI Lab and work with SotA architectures
- build data marts and BI dashboards for monitoring ML models and AI Agents.
Responsibilities
- Development and implementation of AI Agents in production
- Developing end-to-end integrations with external systems and other services via protocols such as Kafka, REST API, gRPC, WS, etc.
- Supporting model and agent releases: documentation, demos, defending solutions from regulators
- Collaborating with business customers, architects, and product teams to develop AI solutions in business.
Requirements
- Work experience as an ML Engineer, DS, MLOps, or Python Backend in ML
- IMPORTANT: Experience in industrial development with Python, knowledge of OOP/design patterns, and experience with microservice architecture
- Experience working with large volumes of data and distributed data storage: e.g., Hadoop
- Experience with frameworks for building AI agents, such as LangChain or LangGraph, basic knowledge of ML/DL
- Proficiency in tools for LLM monitoring and MLOps/ CI & CD.
Will be a plus:
- Experience with distributed task and message queues, stream processing - celery, taskiq, rabbitmq, Kafka, faststream
- Experience developing high-load systems, geo-distributed systems, OpenShift/Kubernetes
- Experience in data engineering.
Conditions
- Comfortable modern office: Saint Petersburg, Ural'skaya str., 1 (shuttle service from the metro is available)
- Work format – office, hybrid by arrangement
- Annual salary review, annual bonus
- Corporate gym and recreation areas
- More than 400 educational programs from SberUniversity for professional and career development
- Onboarding program and manager's assistance at the start
- Extended VHI (voluntary health insurance), preferential insurance for family
- Mortgage for employees
- Free SberPrime+ subscription, discounts on products from partner companies
- Referral bonus for recommending friends to the Sber team.
