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Braze is the leading customer engagement platform helping brands build personalized messaging experiences across push, email, in-app, and more at massive scale. The In-Memory Databases & Observability team provides foundational infrastructure and tools that keep Braze fast, reliable, and observable.
As a Senior Platform Software Engineer, you will design, build, and operate Redis/Valkey, Memcached, Elasticsearch, and observability systems on Kubernetes with a focus on reliability, performance, and cost efficiency at scale. You'll write software that manages these systems including Kubernetes operators, automation, CLIs, and self-serve tooling that replace manual operations.
Key responsibilities include:
- Design and operate Redis/Valkey, Memcached, Elasticsearch and observability systems on Kubernetes
- Build automation, tooling, and services that make these systems reliable and easy for other engineers to use
- Own and evolve Braze's observability platform, including metrics collection, long-term storage, alerting, and dashboards
- Lead capacity planning, upgrades, and migrations for large stateful systems with minimal customer impact
- Partner with engineering teams across Braze to improve system usage, from data modeling to query performance
- Investigate complex production issues and turn learnings into durable fixes and better tooling
- Contribute to on-call rotation and improve runbooks and incident response tooling
- Document designs and decisions clearly for a global team
The role operates at significant scale: Braze's Valkey fleet serves around 36 million operations per second while holding terabytes of data in memory.
REQUIREMENTS:
- 5+ years of experience in software engineering, platform engineering, or SRE with a strong record of writing production code
- Hands-on experience running stateful, distributed systems in production at scale
- Strong working knowledge of Kubernetes and infrastructure-as-code (Terraform, Pulumi)
- Proficiency in at least one general-purpose language such as Go, Python, or Ruby
- Systems mindset: think about interfaces, failure modes, and edge cases; debug methodically
- Strong problem-solving mindset and track record of working with other teams on complex engineering problems
- Clear written and verbal communication; comfort collaborating across time zones
- Bias toward fixing what's broken instead of working around it
NICE TO HAVE:
- Deep experience with Redis/Valkey, Elasticsearch, or similar systems including performance tuning, replication, and failure handling
- Experience with OpenTelemetry and observability tools such as Prometheus, Thanos, Grafana, or Datadog
- Experience with Kafka or other streaming systems
- Experience building developer-facing tooling or Kubernetes operators
- Thoughtful approach to using AI tools in engineering workflow
