Scaling, resiliency, reliability, performance, and efficiency
Build & integrate software
Increase automation
Production Engineering at Pinterest blends systems and software engineering with a focus on scaling, resiliency, reliability, performance, and efficiency
Job Summary
Production Engineering at Pinterest blends systems and software engineering with a focus on scaling, resiliency, reliability, performance, and efficiency.
Lead engineers to deliver impactful work, drive technical architecture discussions, and foster an inclusive and supportive team environment.
Utilize AI to accelerate analysis and iteration while maintaining high standards for quality and correctness.
Matching Summary
Production Engineering at Pinterest blends systems and software engineering with a focus on scaling, resiliency, reliability, performance, and efficiency.
Salary
$164,695—$339,078 USD
Skills & Requirements
Must-have
scaling, resiliency, reliability, performance, and efficiency
build & integrate software
increase automation
infuse best practices into products
develop short and long term embedded engagements
reduce toil and KTLO impact
use AI to accelerate analysis and iteration
foster open and honest communication
empower engineers for career development
develop strong partnerships with Product & Program Management
establish team norms around planning and execution
customer obsession
high integrity and ownership
strong domain expertise in reliability concepts
innovate and provide thought leadership
thrive in ambiguous environments
ruthlessly prioritize highest impact projects
bias toward action and quick decisions
Nice-to-have
align with goals of broader Production Engineering organization
inspire team charter and direction
celebrate unique experiences
embrace flexibility
augment creativity with AI
amplify impact with AI
Key Requirements
3+ years experience managing teams in SRE, Production Engineering, or Platform/Infrastructure
Familiarity with SDLC concepts and tools
Familiar with data platform technologies
Hands-on familiarity with public cloud platforms (AWS, GCP, or Azure)
Knowledge of Linux systems internals and networking
Familiarity with infrastructure technologies (Docker, Kubernetes, Tensorflow, ElasticSearch, ZooKeeper)