Bočkarev Breweries** Moscow Experience: Over 6 years

Employment with an accredited IT company.

Responsibilities:

· Responsible for the development and implementation of the AI strategy in the company.

· Identify the needs and tasks of business units that can be effectively solved with AI tools. Translate business needs into specific AI cases with a positive business case.

· Manage the portfolio of AI initiatives. Responsible for the implementation of approved AI initiatives in accordance with the strategy.

· Build effective interaction with business functions and company management on issues ranging from popularizing AI technologies to evaluating satisfaction with implemented services.

· Increase employee awareness of the capabilities of AI technologies, the potential value of their implementation, and their features and limitations in application, conduct necessary informational and training events.

· Formulate teams of specialists for the implementation of AI projects, including attracting in-house employees and teams or searching and hiring, develop the functional competencies of employees and teams.

· Independently develop AI tools and create/configure them using available corporate platforms.

· Interact with external partners (vendors, integrators, research centers, startups) for the implementation of AI solutions.

And you have:

· Practical experience in transforming business processes using AI

· Experience in leading AI teams/directions and implementing AI projects – from idea to industrial scaling.

· Experience in transforming development teams using AI platforms

· Understanding of the software development lifecycle, knowledge of agile development principles, prototyping, and minimum viable product development.

· Knowledge of project management methodologies, product approach, testing, and hypothesis testing for product development, strong project and portfolio management skills.

· Experience in setting requirements for Data Engineering, Data Science, ML Engineering, Development, IT.

· Practical experience with corporate AI platforms, understanding of architectures and components, advantages and disadvantages of various platforms.

· Understanding of target AI solution architectures and the ability to discuss them with IT and business.

· Technical knowledge:

• Python – practical proficiency at the level of developing product AI services;
• Knowledge of basic ML algorithms: regression, classification, clustering, neural networks. Understanding of the complete ML model building cycle.
• Knowledge of frameworks: TensorFlow, PyTorch, scikit-learn.
• Experience in developing solutions (prototypes and production) based on ML and LLM (OpenAI (GPT), Llama, GigaChat, and similar).
• Knowledge of tools for finetuning, RAG, prompt engineering.
• Experience in deploying, monitoring, and supporting models (SaaS and on-premise).

· Skills in structuring, visualizing, and presenting information, conveying technical concepts in simple language.

· Negotiation and conflict resolution skills.