fulltime • (Hybrid – 3 days on-site / 2 days remote after onboarding) • Brno • Hybrid / Remote
We are looking for a senior platform engineer to help us design, build, and operate high-throughput backend services and data-processing infrastructure for mission-critical systems.
The work is focused on production services that process large volumes of real-time traffic, require strong reliability and scalability, and need to behave correctly under demanding operational conditions.
We are especially interested in someone who has experience with mission-critical systems handling thousands to tens of thousands of requests per second, high-availability architecture, and production environments where latency, correctness, observability, and resilience matter.
Experience from banking, fintech, payments, fraud prevention, transactional platforms, security infrastructure, or similarly high-stakes domains is highly relevant.The right person should be comfortable not only writing code, but also designing systems, owning production reliability, making architectural trade-offs, debugging complex issues, and improving how the platform behaves over time.
What You’ll Work On
- Design, build, and operate high-throughput backend services for security-critical workloads
- Build real-time and near-real-time ingestion, processing, and data-delivery pipelines
- Improve scalability, reliability, and fault tolerance across production services
- Work on systems with high-availability expectations, including 99.99% availability targets
- Design APIs, workers, queues, streams, caching strategies, database schemas, indexes, and data models for large-scale workloads
- Operate queue- and worker-based processing using Redis, Redis Streams, BullMQ, and background consumers
- Improve how the system behaves under load, during traffic spikes, and when downstream dependencies fail
- Own and improve production observability through metrics, logs, traces, dashboards, alerts, and meaningful operational signals
- Manage and improve cloud infrastructure, Kubernetes workloads, deployment automation, autoscaling, and production cluster operations
- Support incident response, performance tuning, capacity planning, production debugging, and post-incident improvements
- Help make architectural decisions that balance speed, simplicity, correctness, and long-term maintainability
This Might Be for You If
- You have already worked on production systems where reliability, latency, correctness, and operational discipline mattered
- You are comfortable taking ownership of complex backend or platform problems without needing every step defined in advance
- You can look at an existing system, understand its bottlenecks, and propose practical improvements
- You think in terms of trade-offs: simplicity vs. scalability, latency vs. consistency, speed of delivery vs. long-term reliability
- You care about how systems behave in production, not only how they are implemented in code
- You have experience debugging difficult issues across multiple layers of the stack, from application code to infrastructure and data stores
- You are pragmatic about architecture and know when a system needs a small fix, deeper refactoring, or a more fundamental redesign
- You can communicate technical decisions clearly and help other engineers understand the reasoning behind them
- You enjoy working with teams that want to raise their engineering maturity around reliability, observability, scalability, and production operations
- You are comfortable contributing both hands-on implementation and higher-level technical direction
- You are highly effective with AI-assisted software engineering tools like Claude Code, Cursor, and opencode, but you know when to rely on engineering judgment instead of LLMs. We value high-quality shipping, not vibe coding.
Technologies & Tech Stack
Our current stack includes:
- Backend: TypeScript, Node.js, NestJS
- Edge & Cloud: Cloudflare Workers, Google Cloud Platform, Cloud Run, GKE
- Databases: PostgreSQL, Drizzle ORM, Firebase / Firestore
- Queues & Caching: Redis / Google Memorystore, Redis Streams, BullMQ
- Data & Search: BigQuery, Elasticsearch
- Infrastructure: Terraform, Helm, Docker, DevSpace
- Observability: Sentry, OpenTelemetry, Prometheus / Google Managed Prometheus, Grafana
You do not need to have used every tool in our stack before. Strong fundamentals matter more than exact tool overlap.
What matters most is experience with backend systems, distributed processing, production operations, observability, and database-backed services at scale. We are looking for someone who understands how production systems fail, how to debug them, and how to make them more reliable over time.
16.07.2026
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