Staff Backend Engineer, Ads Platform

Fetch•Remote,

4d•Hybrid

About The Position

Fetch is building the next generation of systems that power personalized advertising experiences for millions of users, and we're looking for a Staff Backend Engineer to help design and evolve the backend systems behind them. You will build and scale the high-throughput, low-latency distributed systems that sit on the critical path of Fetch's advertising platform, powering real-time decisions and experiences under demanding requirements for latency, availability, correctness, efficiency, and operational resilience. At Fetch, Staff means impact well beyond a single team. You set technical standards that multiple teams adopt, architect across multiple services and domains for company-wide programs, and define multi-quarter initiatives that shape the direction of the broader Ads organization and the Platform, Data, and ML teams it depends on. You are the person who resolves the high-ambiguity, team-spanning problems others get stuck on, and you lead through technical influence and mentorship rather than formal authority. The role requires deep expertise in distributed systems and backend architecture, along with a track record of solving difficult performance and scaling problems in production. You should be comfortable reasoning about systems operating at high request volumes, identifying bottlenecks across the stack, and designing architectures that continue to perform as traffic, data volume, and product complexity grow. This is a high-impact role at the intersection of distributed systems, real-time decisioning, and monetization, where performance, reliability, and operational excellence are non-negotiable. You will work closely with Ads, Product, Platform, Data, and ML teams to build scalable foundations that let Fetch move quickly while holding a high bar for system quality. This is a full-time role that can be held from one of our US offices or remotely in the United States.

Requirements

Proven track record designing, building, and operating distributed backend systems at significant production scale, with demanding throughput, latency, availability, and reliability requirements.
Deep understanding of distributed systems: partitioning, replication, consistency, caching, concurrency, asynchronous processing, failure isolation, and coordination.
Strong track record diagnosing performance and scaling problems across applications, databases, caches, queues, networks, and infrastructure.
Strong expertise in API design, service boundaries, event-driven architectures, and data-intensive systems (streaming, messaging, distributed stores, caching).
Demonstrated ownership of architecture for complex distributed systems, including scalability planning, performance optimization, failure modes, and long-term evolution.
Experience building highly reliable production systems with comprehensive observability: metrics, tracing, structured logging, alerting, capacity planning, and incident response.
Experience making architectural decisions involving scalability, reliability, latency, consistency, operational cost, complexity, and developer-productivity tradeoffs.
Ability to independently translate ambiguous product and business requirements into robust backend designs with clear technical and operational tradeoffs.
Org-level influence beyond direct ownership: standards adopted by multiple teams, architecture for company-wide programs, and mentoring senior engineers across boundaries.
Track record of defining and delivering multi-quarter, cross-team initiatives that shaped org direction and resolved high-ambiguity problems.
Experience leading significant refactoring, migration, or system-health work that improved a team or group's velocity and reliability.
Fluency in modern backend and infrastructure ecosystems such as Kubernetes, event streaming, distributed data stores, cloud infrastructure, CI/CD, and observability tooling.

Nice To Haves

Direct experience building or scaling advertising, ad-serving, auction, marketplace, recommendation, or other real-time decisioning systems.
Familiarity with advertising concepts such as targeting, pacing, bidding, frequency management, attribution, incrementality, and measurement.
Experience operating at very high request rates with strict tail-latency requirements.
Experience designing multi-region or highly available distributed systems and planning for traffic growth, regional failures, and capacity constraints.
Experience building backend infrastructure that supports real-time ML inference, ranking, recommendation, targeting, or personalization.
Demonstrated success improving system throughput, latency, reliability, or infrastructure efficiency at significant production scale.
Strong judgment about distributed systems complexity, including when sophisticated patterns are necessary and when simpler designs scale further and operate more reliably.
Prior Staff-level experience driving architectural direction across multiple teams, services, or product domains.

Responsibilities

Own architecture across critical Ads services. Design the high-throughput, low-latency services behind ad selection, targeting, pacing, delivery, attribution, and measurement, including the calls on partitioning, caching, consistency, concurrency, and performance across multiple services and domains.
Design for reliability, resilience, and operational excellence. Build systems that degrade gracefully under partial failures, traffic spikes, and downstream degradation, with the metrics, tracing, SLOs, and alerting that give clear visibility into revenue-generating systems.
Evolve event-driven and data-intensive architectures. Design reliable data flows across transactional and non-transactional stores, streaming, messaging, caching, and real-time processing, balancing consistency, durability, latency, scalability, and operational complexity.
Set standards multiple teams adopt. Drive backend, reliability, and performance standards across Ads and adjacent teams, and build reusable services and patterns that cut duplication and accelerate development.
Drive engineering leverage. Lead significant refactoring, migration, and system-health work, and build shared infrastructure and patterns that improve the group's velocity and reliability.
Shape org-level technical direction. Define and deliver multi-quarter initiatives that shape Ads-org direction and influence org-level priorities, and carry technical direction for the group when needed.
Solve high-ambiguity, team-spanning problems. Resolve complex reliability, performance, and scalability problems that span multiple teams, and partner across Ads, Platform, Product, Data, and ML to align investment and surface misalignments early.
Raise the engineering bar across teams. Mentor senior engineers across boundaries, lead technical design reviews, and establish practices for distributed systems, performance, reliability, and operational readiness that other teams adopt.