Software engineer
- Location
- San Francisco
- Type
- Full time
- Compensation
- $150k-$200k
- Posted
- 2 days ago
Join a team building useful software. Work closely with engineering and design to turn new ideas into products.
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3-5+ years of software development experience, including building and operating production systems or large-scale distributed services.
Proficiency in C++, Java, GO, Rust, with solid foundations in data structures, algorithms, software design, and performance optimization.
Deep expertise in distributed systems design, including scalability, resiliency, concurrency, fault tolerance, service communication, and API design.
Proven experience with cloud-native technologies, including containers, Kubernetes, CI/CD pipelines, Infrastructure-as-Code, and automated testing frameworks.
Experience building observability solutions using metrics, distributed tracing, centralized logging, dashboards, and alerting systems.
Familiarity with AI-assisted development tools and a proactive approach to adopting AI-first engineering practices.
Strong problem-solving, communication, collaboration, and ownership skills.
Experience building or operating distributed storage systems, object storage, metadata services, or distributed databases.
Knowledge of distributed metadata management, partitioning, replication, consistency models, and recovery mechanisms.
Experience optimizing cloud-scale services for latency, throughput, scalability, and availability.
Experience operating globally distributed services across multiple regions and availability domains.
Familiarity with OCI or other cloud infrastructure platforms, containers, and deployment automation.
Experience developing AI-powered automation for software engineering, testing, debugging, or production operations.
Build and enhance foundational metadata infrastructure supporting OCI Object Storage.
Improve the scalability, performance, reliability, and operational efficiency of distributed storage services.
Deliver critical infrastructure capabilities while maintaining high standards for software quality and production readiness.
Accelerate engineering productivity through AI-assisted development, automation, andcontinuous improvement.
Raise engineering quality and technical standards through mentorship, architectural leadership, and continuous improvement initiatives.
AI-first mindset: Incorporate AI-assisted tools into daily engineering workflows while applying sound engineering judgment.
Ownership and accountability: Take responsibility for software quality, production reliability, and operational excellence.
Engineering excellence: Emphasize clean code, automated testing, observability, security, and maintainability.
Collaboration: Work closely with engineers, architects, and partner teams through design reviews, code reviews, and knowledge sharing
Distributed Systems Engineering: Design, develop, and optimize high-performance distributed metadata service focusing on scalability, consistency, resiliency, and low latency.
Reliability and Fault Tolerance: Build resilient infrastructure using replication, redundancy, failure recovery, and automated failover mechanisms.
Infrastructure Automation: Lead automation initiatives across the software development lifecycle, including CI/CD, testing frameworks, deployment automation, and Infrastructure-as-Code.
Production Operations: Support production services through monitoring, troubleshooting, incident response, root cause analysis (RCA), and on-call rotations.
Observability and Performance: Drive reliability, scalability, and operational readiness through capacity planning, incident response, root cause analysis, and continuous improvement.
AI-First Engineering: Actively leverage AI tools for coding, debugging, testing, code reviews, incident analysis, and workflow automation to improve engineering velocity and quality.
Engineering Excellence: Own features end-to-end, participate in design and code reviews, maintain technical documentation and runbooks, and collaborate with engineers and architects to deliver reliable cloud infrastructure.
Technical Leadership and Mentorship: Mentor engineers, influence technical strategy across organizations, and help raise the engineering bar through design reviews and technical leadership.