Staff Software Engineer

The role

This Staff Software Engineer will design, build and operate forecasting, recommendation and agentic AI systems in production. The role includes owning services end-to-end, including on-call and incident resolution, and giving technical leadership across teams.

What you will do

• Design, build, and operate systems supporting forecasting, recommendations, and agentic AI workflows in production.
• Write production-quality code daily; own services end-to-end from design through on-call and incident resolution.
• Architect low-latency, high-throughput SaaS services, including APIs, data pipelines, model inference, and agent orchestration.
• Build and maintain production-grade agentic applications, including tool-using agents, workflow orchestration, and guardrails.
• Work with foundational LLMs such as GPT, Claude and Gemini Pro, selecting models and deployment patterns based on latency, cost and reliability.
• Champion observability and reliability: metrics, logging, tracing, alerting, and post-incident analysis.
• Lead and participate in production incident response, retrospectives, and systemic fixes.
• Identify architectural risks early and make design decisions that prevent outages and scalability issues.
• Reduce complexity across services, infrastructure, and processes to improve stability and team velocity.
• Provide technical guidance across teams and participate in architectural reviews beyond your immediate domain.

Required qualifications

• 12+ years of professional software engineering experience building and operating production-grade distributed systems.
• Strong track record of hands-on ownership of business-critical services, with measurable improvements in latency, throughput, stability, or cost.
• Deep expertise in systems design, including service boundaries, concurrency, data modeling, failure handling, and scalability tradeoffs.
• Production experience supporting machine learning-driven systems (forecasting, recommendations, or similar), with emphasis on serving, pipelines, and infrastructure.
• Expert-level experience with AWS, including designing, deploying, and operating large-scale cloud-native systems.
• Strong hands-on experience with Kubernetes, containerized microservices, and modern CI/CD pipelines.
• Experience operating software in both on-prem data center and AWS cloud environments.
• Fluency with modern AI-assisted development tools such as Cursor and GitHub Copilot.
• Proficiency in one or more backend languages for large-scale systems (Python, Java, Go, or Scala).
• Bachelor's or master's degree in computer science, Mathematics, or a related field, or equivalent practical experience.

About the company

Zeta Global is a publicly traded (NYSE: ZETA) AI-powered marketing technology company. It combines a large proprietary consumer data set with artificial intelligence to help enterprise brands acquire, grow and retain customers.