About the project
We are a leading classifieds platform, holding the #1 position in Uzbekistan. Our platform serves over 6 million active users per month (MAU) and manages a database of 2.2 million active listings.
The project has entered a new phase: we are building our own independent local platform — migrating some services and designing and developing others from scratch. Search & Recommendations is a strategically important area: the quality of search and relevance of recommendations directly impacts conversion, retention, monetization, and, essentially, the user's perception of the entire product. This is one of the areas where the company is investing first.
Your mission
Become the technical owner of the direction and IT partner to the Product Manager: together, you are responsible for the area as a unified tandem — the PM holds the product vision and business priorities, while you ensure that this vision is technically feasible, scalable, and delivered to production quickly and with high quality. You translate product goals into architecture and roadmap, highlight technical possibilities and limitations, and participate in shaping the strategy of the direction on equal footing.
This is a player-coach role: approximately 50% of the focus is on people, processes, prioritization, and working with the PO; 50% is hands-on development, architecture, and participation in the most complex tasks alongside the team.
Responsibilities
Partnership with Product
- Working in tandem with the Product Owner of the direction: joint prioritization, feasibility assessment, finding technical opportunities for product hypotheses.
- Translating business goals into a technical roadmap and back — clearly explaining trade-offs to the product side.
- Participating in shaping the strategy of a strategically important direction, not just executing it.
Leadership and Team
- Developing and growing the team (hiring, onboarding, 1:1s, development plans, culture of engineering autonomy).
- Owning the technical roadmap: decomposition, balancing delivery, search quality, and technical debt.
- Responsibility for the direction's metrics: search result relevance, latency, stability, impact on product KPIs.
Hands-on Technical Leadership
- Personal involvement in development: writing code in key and complex parts of the system, not just reviewing.
- Architectural ownership of the search core: configuring, optimizing, and scaling Solr Cloud in an AWS EKS environment.
- Multilingual search: quality for Uzbek (Cyrillic/Latin) and Russian languages — morphology, synonyms, transliteration.
- Implementing hybrid search with semantic vectors (embeddings) to improve search accuracy.
- Developing personal ranking (LTR) based on behavioral data stream from the Data Platform.
- High-load optimization: tuning for peak loads, distributed caching, observability, and SLO.
Requirements
- Player-coach: you have led an engineering team but continued to write code — you can combine management, mentoring, and personal technical contribution.
- Partnership with Product: experience working closely with a Product Owner / product team, ability to speak the language of business and find compromises without sacrificing engineering quality.
- Experience in Big-Ecom / High-Load: successfully solved search problems in high-load projects of the level of Yandex, Avito, Ozon, Wildberries, Lamoda, Auto.ru, ASOS, Wolt, or similar.
- Deep Search Expertise: understanding the internal workings of Apache Solr (or Elasticsearch/OpenSearch with willingness to dive into Solr) — custom plugins, complex indexing schemes, deep performance tuning.
- Mastery in Go: confident command of Golang for high-performance microservices around the search core.
- Conversational: understanding the principles of building conversational search systems; practical experience or conceptual understanding of how to integrate a search engine with LLMs, RAG architecture, and intent detection mechanisms.
- Vector & Personalization: practical experience with vector search and user behavior-based ranking algorithms.
- Infrastructure: understanding cloud infrastructure (AWS) and containerization (Kubernetes/EKS).
- Engineering Maturity: ability to balance speed, quality, and technical debt; establishing processes for review, testing, and releases.
Will be a plus
- Experience launching search/recommendations from scratch or during migration/carve-out.
- Working with multilingual and morphologically complex languages.
- Experience collaborating with ML teams and integrating ML models into production search.
- Experience designing custom skills, rules, playbooks, or project instructions for AI agents.
- Experience configuring subagents, permissions, tool access, and secure agent interaction scenarios with the codebase.
- Experience building agent-ready documentation for large backend / search / data projects.
- Experience migrating or refactoring large systems using AI agents.
- Experience implementing an AI-First / agent-driven approach in an engineering team.
Technological Context
- Search: Apache Solr (primary engine), vector search.
- Backend: Go.
- Infrastructure: AWS, Kubernetes/EKS.
- Data: proprietary Data Platform as a source of signals for ranking.
AI Agent Development Experience
- Practical experience in development using AI agents.
- Understanding of harness management for controlled, predictable, and verifiable AI agent operation.
- Experience with the spec-first approach: first, describe requirements, contracts, architectural decisions, and project structure, then generate and refine code using the agent.
Conditions
What we offer:
- Participation in the project's development from the start.
- Direct impact on the final product.
- Professional and career growth prospects.
- Development within a team of experienced colleagues.
- Minimal bureaucracy and quick decision-making.
- Individual discussion of working hours and format with each employee.
