Pinterest
Staff Software Engineer, Service Communications
engineeringfull-timeSan Francisco, CA, US; Remote, US
SALARY
Not listed
WORK TYPE
remote
JOB TYPE
full-time
INDUSTRY
general
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About the role
What you'll do:
- Architect and deploy advanced service mesh features, focusing on service discovery, traffic shaping, and deep observability using Envoy proxy.
- Lead the organization-wide adoption of service identity and mTLS to satisfy critical AAA security requirements for service-to-service paths.
- Design traffic optimization primitives like locality-aware routing to materially reduce data transfer costs for high-volume service traffic.
- Maintain and modernize service framework libraries in Java, Python, and C++, enhancing the developer experience and operational reliability.
- Collaborate with service owners across the company to drive adoption and refine infrastructure requirements for emerging feature needs.
- Partner with infrastructure peers on multi-region and multi-cloud strategies that rely on robust service communication primitives.
- Use AI to accelerate analysis and iteration, while applying judgment and verification to ensure correctness and quality.
- Join the team oncall rotation to manage incident response, perform post-mortems, and drive long-term reliability improvements.
What we're looking for:
- 6+ years of infrastructure or platform engineering experience, specifically within distributed systems or RPC framework development.
- Deep technical expertise in service mesh technologies such as Envoy or Istio, including hands-on experience with L7 proxying.
- Proficiency across multiple languages (Java, Python, C++) and a track record of building internal libraries or developer tools.
- Strong understanding of service security, including mTLS adoption and identity management via SPIFFE/SPIRE.
- Proven ability to design highly available and efficient distributed systems at massive scale.
- Demonstrated experience driving the adoption of complex platform capabilities across diverse cross-functional engineering teams.
- Demonstrated experience using AI to accelerate engineering workflows, with a clear approach to validating accuracy and quality.
- Bachelor’s/Master’s degree in Computer Science, a related field, or equivalent experience.
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