We are looking for a Backend Engineer to join a growing group! Our Alerting backend powers real-time, streaming-based detection at massive scale, processing millions of events per second with millisecond latency to catch issues as they happen. Built with a distributed, event-driven architecture, it supports complex pattern evaluation, dynamic enrichment, and fault-tolerant delivery for mission-critical observability.
What You'll Do:
Lead the design, development, and evolution of scalable, high-impact systems.
Own features end-to-end, ensuring predictable production behavior from design through deployment.
Solve complex technical challenges at scale using sound engineering principles and modern stream processing technologies.
Collaborate closely with engineers and product managers to continuously improve the product.
Drive both technical excellence and meaningful user outcomes.
Requirements:
Requirements:
5+ years of software development experience.
3+ years of development experience with JVM stack – Java / Kotlin / Scala – Advantage.
3+ years of experience developing and operating distributed systems in production.
Proven experience in building systems that are highly available and reliable through strong architectural practices, monitoring, and proactive incident management.
Hands-on experience with Data Streaming technologies, including Apache Kafka, Spark Streaming, KafkaStreams, or Apache Flink.
Proficiency in data modeling and designing systems to handle large-scale, distributed datasets efficiently.
Strong knowledge of distributed computing paradigms and principles, such as consistency, partitioning, and resilience.
B.Sc. in Computer Science or an equivalent field.
Requirements:
5+ years of software development experience.
3+ years of development experience with JVM stack – Java / Kotlin / Scala – Advantage.
3+ years of experience developing and operating distributed systems in production.
Proven experience in building systems that are highly available and reliable through strong architectural practices, monitoring, and proactive incident management.
Hands-on experience with Data Streaming technologies, including Apache Kafka, Spark Streaming, KafkaStreams, or Apache Flink.
Proficiency in data modeling and designing systems to handle large-scale, distributed datasets efficiently.
Strong knowledge of distributed computing paradigms and principles, such as consistency, partitioning, and resilience.
B.Sc. in Computer Science or an equivalent field.
Advantage:
Familiarity with gRPC and Protobuf.
Hands-on experience with RocksDB optimizations and tuning.
Production experience in a SaaS environment – Metrics, Logging, Troubleshooting production systems.
This position is open to all candidates.
