Staff Backend Engineer - Exposure Management Lead (Remote)

Censys

Little Canada (MN)

Remote

USD 140,000 - 190,000

Full time

5 days ago
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Job summary

Censys is seeking a Staff Backend Engineer to lead the Exposure Management team and guide a migration from legacy ASM to a next-generation platform. You will own backend services, drive architectural decisions, and mentor a growing engineering group on scalable, real-time data processing.

You will work across architectures, leverage Go as the primary backend language, and apply AI/LLM techniques to improve efficiency and product capabilities, while balancing legacy commitments with long-term

Qualifications

  • 10+ years of experience in software engineering.
  • 5+ years of experience with Go.
  • Strong distributed systems background.
  • Experience with service-oriented architectures and the operational stack to support them (gRPC/REST, microservices, GCP, Kubernetes).

Responsibilities

  • Serve as the Tech Lead for the Exposure Management team, driving technical direction across services.
  • Own the migration plan and execution to bring legacy ASM functionality onto the new platform.
  • Take end-to-end ownership of backend services, resolving legacy behavior and ensuring interoperability with the new platform.
  • Drive technical alignment across shared systems, improving coordination and engineering effectiveness.
  • Mentor the team and uphold high engineering standards.
  • Leverage AI and LLM technologies to improve engineering efficiency and capabilities.

Skills

Go
Distributed systems
Microservices
GCP
Kubernetes
GRPC/REST
Architectural leadership

Tools

Kubernetes
GCP
GRPC
REST

Job description

Censys is seeking a Staff Backend Engineer to lead the Exposure Management team and guide a migration from legacy ASM to a next-generation platform. You will own backend services, drive architectural decisions, and mentor a growing engineering group on scalable, real-time data processing.

You will work across architectures, leverage Go as the primary backend language, and apply AI/LLM techniques to improve efficiency and product capabilities, while balancing legacy commitments with long-term

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