Senior Software Engineer (Backend)
RZR Global Inc.
Who Are We? RZR is an AI-native advertising platform built for the next era of performance marketing. We operate at the intersection of machine learning, programmatic media, and full-funnel mobile growth, powering campaigns for some of the world's most ambitious advertisers. Our platform is purpose-built to deliver outcomes at scale, not just impressions. We are a team of builders, operators, and technologists who believe the advertising industry is overdue for a fundamental rethink. We move fast, operate with a high degree of ownership, and hold ourselves to an exceptionally high standard of craft. RZR is scaling aggressively with an active M&A pipeline and a platform vision that puts us on a path to becoming an industry leader. This is a rare opportunity to join a company at an inflection point and help shape what it becomes.
Role Overview We are looking for a Software Engineer or Senior Software Engineer (Backend) to join our core engineering team in San Francisco. You will work on the systems that sit at the heart of our programmatic Demand-Side Platform (DSP) - the real-time bidding engine that processes millions of bid requests per second with sub-100ms latency requirements. This is infrastructure that directly moves revenue. You will work alongside data scientists, infrastructure engineers, and product stakeholders to build and evolve the systems that power real-time bidding, machine learning inference, and ad delivery at scale. The role is hybrid, with the team collaborating in person on Monday, Tuesday, and Friday at our San Francisco office.
Key Responsibilities
Role Overview We are looking for a Software Engineer or Senior Software Engineer (Backend) to join our core engineering team in San Francisco. You will work on the systems that sit at the heart of our programmatic Demand-Side Platform (DSP) - the real-time bidding engine that processes millions of bid requests per second with sub-100ms latency requirements. This is infrastructure that directly moves revenue. You will work alongside data scientists, infrastructure engineers, and product stakeholders to build and evolve the systems that power real-time bidding, machine learning inference, and ad delivery at scale. The role is hybrid, with the team collaborating in person on Monday, Tuesday, and Friday at our San Francisco office.
Key Responsibilities
- Design, develop, and maintain high-performance backend services for our real-time ad bidding platform
- Build and optimize distributed systems capable of handling millions of queries per second with sub-100ms latency
- Work closely with data scientists to integrate and deploy machine learning models into production environments
- Improve system scalability, observability, and fault tolerance through clean architecture and metrics-driven design
- Collaborate with cross-functional teams to align technical execution with product goals
- Participate in peer code reviews, technical design reviews, and performance debugging sessions
- Write clean, maintainable, well-tested code and contribute to raising the bar on engineering quality
- Mentor junior engineers and help shape team practices as we scale
- 3+ years of backend development experience, ideally in low-latency or distributed environments
- Proficiency in Rust, C++, Go, or Java with hands-on production experience
- Strong knowledge of multithreading, concurrency, memory management, and network I/O
- Experience with distributed systems: message queues, sharding, replication, and failover strategies
- Comfort with profiling tools, performance benchmarking, and distributed tracing
- Familiarity with CI/CD pipelines and containerized deployment (Docker/Kubernetes a plus)
- Familiarity with real-time bidding, ad tech, or financial trading systems is a strong plus
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field
- Work at the core of a revenue-critical system - our bidding engine is not a side project; it is the product, and your work directly determines its performance and reliability
- True low-latency systems engineering at scale - the depth of algorithmic and performance challenges here is rare; if you enjoy systems-level thinking, this is the environment for it
- Small, senior team with real autonomy - you will own features end-to-end, from design through production, and have a direct line to engineering leadership
- At the intersection of ML and infrastructure - you will collaborate with machine learning experts on real-time model inference, a technical problem space few backend engineers get exposure to
- A platform in active transformation - we are modernizing toward full multi-datacenter redundancy, Kubernetes-based autoscaling, and faster deployment cycles; you will help shape the architecture, not just execute it
Vacancy posted 13 hours ago
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