Senior Software Engineer — AdTech
Zeta GlobalLondon, UKPosted 6 April 2026
Job Description
WHO WE ARE
Zeta Global (NYSE: ZETA) is the AI-Powered Marketing Cloud that leverages advanced artificial intelligence (AI) and trillions of consumer signals to make it easier for marketers to acquire, grow, and retain customers more efficiently. Through the Zeta Marketing Platform (ZMP), our vision is to make sophisticated marketing simple by unifying identity, intelligence, and omnichannel activation into a single platform – powered by one of the industry’s largest proprietary databases and AI. Our enterprise customers across multiple verticals are empowered to personalize experiences with consumers at an individual level across every channel, delivering better results for marketing programs. Zeta was founded in 2007 by David A. Steinberg and John Sculley and is headquartered in New York City with offices around the world. To learn more, go to www.zetaglobal.com .
The Role
We’re looking for a Senior / Staff DSP Engineer to build and evolve Zeta’s real-time bidding and decisioning systems. This is a hands-on role focused on designing and operating low-latency, high-throughput services that process bid requests, score opportunities, apply pacing and budget constraints, and produce bids within strict SLAs. You’ll work closely with platform, data, and ML teams to integrate retrieval and scoring systems into the bidder while keeping the hot path fast, safe, and observable. This role is ideal for engineers who love distributed systems, performance engineering, and building production-grade systems at extreme scale.
What You’ll Do
Real-Time Bidding Systems: Design and build core DSP bidder components that handle high-QPS bid request ingestion, filtering, enrichment, decisioning, and bid response generation within strict time budgets.
Auction Eligibility Logic: Implement auction logic, campaign/line-item eligibility, targeting constraints, frequency controls, supply quality checks, and policy enforcement.
Low-Latency Engineering: Optimize p99 latency and tail behavior using timeouts, backpressure, concurrency control, efficient serialization, caching strategies, and careful memory/GC management.
Pacing Budgeting: Build and extend pacing and budget management logic (spend controls, throttling, goal-based pacing, safety constraints) and integrate with control-plane services (campaign config, feature flags, budgets).
Scoring ML Integration: Integrate real-time model scoring and feature retrieval systems with production guardrails (shadow mode, A/B tests, canaries, circuit breakers, fallbacks).
Reliability Operations: Define SLOs and observability (metrics, tracing, structured logging), participate in on-call, and drive post-incident improvements.
AWS at Scale: Build and operate services on AWS (compute, networking, autoscaling, streaming, data stores) and partner on cost/performance optimization.
Engineering Leadership (Staff scope): For staff-level candidates, drive technical direction for parts of the bidder stack (interfaces, service boundaries, performance budgets) and mentor engineers through design/code reviews and best practices.
Senior: 5+ years of software engineering (with substantial backend/distributed systems work). Staff: 8+ years with demonstrated ownership of large-scale, production systems.
Proven experience building low-latency, high-QPS services (real-time decisioning, trading, ad serving, marketplaces, or similar).
Strong proficiency in Java and/or Go for performance-oriented backend development.
Solid understanding of distributed systems fundamentals: consistency trade-offs, caching, failure modes, retries/timeouts, backpressure, load shedding.
Experience operating production services on AWS and making practical cost/performance trade-offs.
Experience with data stores and patterns used in real-time systems (e.g., Redis/Memcached, DynamoDB/Cassandra, Kafka/Kinesis).
Strong debugging skills across services: profiling, tracing, heap/GC analysis, latency investigations.
Clear communicator and colla ... (truncated, view full listing at source)
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