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Описание вакансии
TL;DR
Senior Backend Engineer (AI): Designing and owning scalable distributed systems with an accent on event-driven architecture, domain-driven design, and AI implementation inside performance-critical backend code. Focus on model serving, inference pipelines, vector search, messaging reliability, and optimizing latency, cost, and resource usage.
We're looking for someone to take real ownership of our backend architecture. Not another CRUD service — distributed systems, event-driven design, and AI running inside the backend itself rather than behind someone else's API.
The work
You'd be designing and owning scalable distributed systems end to end, and writing down the reasoning behind your decisions so the rest of the team can follow it — ADRs, diagrams, design reviews. A lot of it is modelling messy business domains properly with DDD and turning them into services that stay clean a year later.
Event-driven work is a big part of the job: Kafka or RabbitMQ, designing topics and queues, thinking through delivery guarantees and what happens when things fail. And on the AI side, actual implementation inside performance-critical code — model serving, inference pipelines, vector search, and the latency and cost tuning that comes with it.
The rest is what you'd expect from a senior role: designing schemas that hold up as data grows, reviewing code, mentoring the people around you, and working closely with product, data and DevOps.
What you need to have
Real architecture experience — microservices, modular monoliths, hexagonal/clean — and opinions about when each one is the wrong choice. A solid grasp of event-driven patterns: event sourcing, CQRS, sagas, idempotency, eventual consistency, message ordering.
Production experience with Kafka or RabbitMQ is non-negotiable. Partitioning, consumer groups, retries, dead-letter queues, delivery semantics — you should have debugged these under load, not just read about them.
You'll also need experience scaling systems horizontally (caching, load balancing, sharding, HA), hands-on AI implementation work (embedding pipelines, RAG, inference optimization, batching, GPU/CPU resource management), practical DDD, and strong database design — indexing, transactions and isolation levels, knowing when SQL beats NoSQL and when it doesn't.
Language-wise, strong proficiency in at least one strictly typed OOP language: Java, C#/.NET or C++. SOLID and design patterns should be part of how you work day to day, including knowing when a pattern is overkill.
Applying
Send your CV and a GitHub or portfolio link to Показать контакты. If you've built something you're proud of, tell us about it — we'd rather read that than a list of technologies.
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