Staff Software Engineer - Log Management

Radiant Security is building the most advanced AI SOC platform, featuring unbounded alert triage, investigation, and response for security teams at scale. Our platform ingests alerts from across an organization's entire security stack (SIEM, EDR, identity, cloud) and uses AI to triage, investigate, and surface what actually matters. We're replacing alert fatigue with clear signal, so analysts can focus on real threats.

We're a small, fast-moving team. We ship continuously, stay close to customers, and hold ourselves to a high standard. Our product touches the daily workflows of security teams, and decisions we make have a direct impact on how quickly threats get resolved.

Join us and boost your career with hands-on AI experience.

As a Staff Software Engineer at Radiant Security, you’ll own the full lifecycle of customer security telemetry — from ingestion to storage in our data lake.
When customers face active incidents, our ingestion pipeline is mission-critical. Reliability and operational excellence here are product requirements, not just engineering ideals.
You’ll drive the scalability and reliability of our ingestion infrastructure, define the architecture of our data lake, and establish the DevOps practices that allow a lean team to evolve safely over time.

• →Own and scale our ingestion platform end-to-end
  Design and operate high-throughput ingestion pipelines with zero-downtime deployment patterns (dual-write, backfills, safe rollback), ensuring resilience under real-world failure modes (backpressure under load spikes, delivery guarantees, DLQs, replay mechanisms) and enforcing strict tenant isolation (per-tenant rate limiting, noisy neighbor prevention, storage partitioning across pipeline and lake layers)
• →Define and evolve our data lake architecture
  Own storage layout, partitioning, schema design, and ensuring efficient high-throughput writes and reliable downstream consumption, while managing lifecycle (compaction, retention, cold storage, cost optimization)
• →Build and operationalize platform foundations
  Develop deployment pipelines for stateful services, per-tenant quota systems, synthetic load testing, and monitoring that the broader engineering team depends on
• →Establish reliability standards and operate in production
  Define and enforce SLOs (latency, durability, availability), including alerting, and incident response, while continuously improving observability and operational excellence
• →Drive technical leadership and platform strategy
  Partner with product and engineering leadership to translate strategic goals into clear requirements and execution plans, while mentoring engineers, setting technical direction, and raising the bar on design, reliability, and operational excellence across the team

• Strong backend and data systems experience
  Proven experience building and operating high-throughput ingestion systems in production, with strong backend programming skills (our stack uses Python, Golang, and Node.js)
• Cloud, streaming, and data platform expertise
  Experience with AWS, GCP, or Azure (S3, GCS, Data Lake), streaming systems (Kafka, Kinesis — including delivery semantics and consumer group management), and large-scale data lake design (partitioning, formats, lifecycle)
• Production-grade infrastructure and reliability practices
  Experience with zero-downtime migrations (dual-write, backfills, safe cutovers), Infrastructure as Code (Terraform, Pulumi), CI/CD (canary + rollback), and operating and monitoring data platforms in production (Prometheus, Grafana, Datadog), including SLO definition and incident response
• Strong distributed systems and storage fundamentals
  Fault tolerance, backpressure handling, graceful degradation, partition tolerance, plus experience with databases, object storage, and performance tuning for high-throughput workloads
• Modern infrastructure stack experience
  Containerization and orchestration (Docker, Kubernetes) for deploying and scaling stateful service

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