Description
We are developing a corporate methodology for the GenAI Production Process and ensuring its support through automation tools. Our key goal is to guarantee that all teams work according to unified yet flexible standards, implement changes faster, and achieve predictable results.
We are building lifecycle management processes for agents and are looking for a person who will help make them mature, scalable, and secure.
Responsibilities
- development of standards and templates for describing requirements for GenAI solutions (business, functional, non-functional)
- implementation of QualityGates and checkpoints for agent processes: security, regulatory compliance, response quality
- project management for implementing key GenAI initiatives in B2C, including piloting new technologies
- collection of feedback from teams, iterative refinement of processes, scaling successful practices
- optimization of the production process based on product metrics: reducing time-to-market, increasing delivery frequency
- building communications with internal customers within the B2C direction, collecting and formalizing needs
- change management: interaction with centralized teams of Sber (GigaPlatform, IDP, Reliability, AI Risk Hub), placing tasks in their backlog, and advocating for the interests of the direction.
Requirements
- work experience in the AI/GenAI domain — required (understanding of the agent lifecycle, RAG, prompt engineering, model limitations)
- work experience as a business analyst or methodologist for at least 3 years, including successful experience in implementing new processes and methodologies
- proficiency in business process design and analysis methods (BPMN, ARIS, IDEF or similar)
- skills in project management and change management, focus on a product approach and metrics
- ability to build communications and find consensus with a large number of stakeholders (from developers to business customers).
Will be an advantage:
- knowledge of MLOps/LLMOps practices, understanding of infrastructure for deploying agents
- ability to automate daily routines using LLM and Low-code / No-code tools (N8N, LangFlow, Flowise, etc.)
- knowledge of Python and the most popular libraries for creating agents (LangChain, LangGraph, AutoGen, etc.).
Conditions
- office: Kutuzovsky Prospekt, 32
- work format – hybrid
- annual salary review, annual bonus
- corporate gym and relaxation areas
- more than 400 educational programs from SberUniversity for professional and career development
- onboarding program and manager 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.
