Backend Engineer

Location: Tokyo

Department: Engineering

Backend engineer - Indigo Platform 

LevelBlue/Cybereason · Tokyo, Japan MUST BE LOCATED IN JAPAN

At Level Blue/Cybereason, we are developing Indigo, our next-generation platform designed for high-throughput ingestion, processing, and real-time analysis of EDR, XDR, and MDR telemetry. The system is architected to handle millions of concurrent security events per second, requiring high-concurrency backend services written primarily in Rust, deployed across low-latency distributed infrastructure. 

We are looking for a Full-Stack Engineer with a strong backend focus to own core components of the Indigo platform, optimizing for data integrity, low latency, and system reliability at scale. 

Key Responsibilities 

• System Architecture & Development: Design, implement, and maintain scalable backend services and supporting front-end interfaces for the Indigo platform. 

• Data Ingestion & Processing: Build and optimize high-throughput data pipelines capable of ingesting and parsing large volumes of real-time security logs and metrics. 

• Performance Optimization: Continuously profile, benchmark, and optimize distributed services to maintain minimal processing latency under heavy workloads. 

• API & Integration Engineering: Design and implement resilient, secure APIs to interface with various enterprise IT and cybersecurity tools. 

• Security & Compliance: Ensure all platform components adhere to strict security standards, incorporating robust encryption, token-based authentication (OAuth 2.0), and data protection protocols. 

Technical Qualifications 

Required Experience 

• Professional Experience: 5+ years of full-stack or backend-heavy development experience building distributed, high-throughput systems. 

• Core Languages: Strong proficiency in Rust is required. Familiarity with Go, Java, or C++ is highly valued. 

• Data Pipelines & Streaming: Hands-on experience with Apache Kafka, the ELK stack, and distributed data processing frameworks (e.g., Flink, Spark, Redis). 

• Infrastructure & Cloud: Proven experience with cloud-native environments, microservices architectures, and containerization (Docker, Kubernetes). 

• Databases: Strong understanding of SQL and NoSQL databases, including optimization for high-write, data-heavy environments. 

• Observability: Familiarity with telemetry routing and monitoring tools like Datadog and Vector. 

Preferred Qualifications 

• Familiarity with SIEM systems or the application of machine learning within data streams. 

• Experience with time-series databases, data warehousing solutions, and GraphQL. 

• Knowledge of Infrastructure as Code (IaC) tools and modern DevOps/SRE practices. 

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