Principal Software Engineer – Sensor, Telemetry & Observability (Hybrid)

CrowdStrike is a global cybersecurity company that protects organizations through its AI-native Falcon platform and lightweight endpoint sensor. The Principal Software Engineer will serve as the senior technical architect for sensor telemetry and observability, owning end-to-end architecture across endpoint collection, cloud ingestion, and analytics. The role will also lead cross-platform systems design, data governance, technical strategy, and mentorship across distributed engineering teams.

Responsibilities:

• Own the architecture and technical strategy for a unified telemetry and observability platform, from endpoint collection SDK to cloud ingestion, decode, and analytics
• Design for the realities of the endpoint: crash-survivable in-memory telemetry, resource-constrained collection, priority stream separation, and performance-sensitive paths
• Drive structured logging and data governance — type safety, PII auditability, and privacy compliance for telemetry collected at scale
• Evolve the platform without breaking existing consumers, and serve as the connective technical authority for telemetry across multiple teams
• Own designs from concept through shipped code, on-endpoint and in-cloud, with cross-platform deliverables
• Lead, mentor, and raise the technical bar across a distributed engineering team

Requirements:

• Deep, hands-on experience architecting at-scale telemetry, observability, or crash-reporting platforms end-to-end — agent SDK through cloud ingestion and analytics — with systems you designed running in production
• Strong low-level and systems engineering in C/C++, with a track record of performance-sensitive, resource-constrained design
• Experience with structured logging, telemetry data governance, and privacy/PII handling at scale
• A record of shipping and evolving platforms without breaking consumers, and of influencing technical direction across teams
• Strong debugging fundamentals: crashes, memory issues, contention, and system performance
• Ability to lead, mentor, and collaborate in a distributed team
• Proven experience utilizing AI technologies to enhance decision-making, streamline workflows and processes, improve efficiency and drive business outcomes
• Scalable, lightweight, high-performance systems and OS internals across more than one platform
• OS-level performance and diagnostic instrumentation (e.g., ETW, PMU/hardware telemetry)
• Data lake and analytics stacks (KQL, SQL, Snowflake) and Go-based cloud services
• Endpoint security domain knowledge; comfort in an Agile, frequently-shipping team