Description
We conduct fundamental and applied research at the intersection of neuroscience, psychology, and behavioral economics to help businesses with AI transformation. Our projects aim to deeply understand how technological changes affect customers, employees, and business processes both within the fintech and financial services ecosystem and in society as a whole.
Key goal of the role:
You are a technical leader who leads end-to-end development of the lab's AI solutions: designs the architecture, sets correct technical tasks for the team and partners, ensures the quality and production-readiness of the solutions. A role at the intersection of strong engineering expertise (CTO-level) and team management.
Responsibilities
- design and develop the architecture of the lab's AI solutions: LLM services, RAG systems, AI agents, data pipelines, APIs, and integrations
- select and justify the technology stack and infrastructure (storage/search, components for RAG and agents)
- be responsible for the quality of the engineering solution: performance, scalability, reliability, security
- organize the full delivery cycle: from idea/prototype to MVP, pilot, and industrial use. Set up and maintain production processes
- define approaches for evaluating the quality of RAG/AI agents: accuracy and usefulness of responses, source grounding, speed, cost, human/automated testing checks
- lead the development team: planning, decomposition, task assignment, deadline and quality control, reviews, employee development. Manage external contractors and partners: create specifications, acceptance criteria, control architecture and delivery quality
- be a technical consultant for stakeholders and internal customers of the ecosystem: explain decisions in simple terms, propose options, document compromises
- maintain technical documentation: architecture diagrams, key decisions, operational instructions, integration and service level requirements (where necessary).
Requirements
- at least 5 years of experience in developing and architecting complex systems (services/integrations/high load)
- confident hands-on skills: Python (or comparable stack) + solid SQL
- experience building RAG systems end-to-end: data preparation - indexing/search - response generation - basic security and quality control
- experience building AI agents and integrating them with external systems (APIs, knowledge bases, corporate services)
- understanding of key GenAI risks and ways to mitigate them: hallucinations, data leaks, prompt injection attacks, source/reference control
- experience with big data and pipelines; understanding of data quality and monitoring
- experience collaborating with data science / ML (or own experience) — ability to set tasks, estimate timelines and risks
- production experience
- ability to translate business tasks into a technical plan: decomposition, prioritization, completion/acceptance criteria
- at least 3 years of experience managing a development team: task assignment, quality control, feedback, development
- strong communication skills: ability to negotiate, clarify, explain complex concepts in simple terms, maintain a healthy team tone.
Conditions
- comfortable modern office in Moscow, near Kutuzovskaya metro station
- opportunity to choose a convenient schedule – office/hybrid
- annual salary review and annual bonus
- corporate gym and recreation areas
- more than 400 educational programs from SberUniversity for professional and career development
- extended voluntary health insurance, preferential insurance for family, and corporate pension program
- flexible mortgage discount equal to 1/3 of the Central Bank's key rate
- free SberPrime+ subscription, discounts on products from partner companies.
