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Zeta Global is seeking a Staff Software Engineer to provide technical leadership for its Forecasting and Recommendations platforms, with a strong focus on production-grade AI and agentic systems. This is a hands-on role centered on designing, building, and operating high-throughput, low-latency distributed systems that power forecasting, recommendations, and AI-driven decisioning at scale.
You will work deeply in backend systems, infrastructure, and AI application architecture while remaining accountable for reliability, observability, and operational excellence. The ideal candidate has shouldered real production incidents and brings strong judgment around building stable, observable, and scalable systems, including modern agentic and LLM-powered applications.
Key responsibilities include:
- 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 fluently with foundational LLMs (GPT, Claude, Gemini Pro), selecting appropriate models and deployment patterns based on latency, cost, and reliability tradeoffs
- Use frameworks such as LangChain and voice agents to accelerate development while enforcing production discipline
- Embrace AI-assisted development workflows (Cursor, GitHub Copilot) to move quickly without sacrificing quality
- Champion observability and reliability through 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
Staff-level expectations include being a prolific, hands-on contributor who raises the bar through example; owning and deeply understanding large portions of the codebase and system architecture; simplifying complex systems to increase team velocity and reliability; balancing technical, analytical, and product constraints to deliver pragmatic solutions; setting short- to medium-term (6–12 month) technical direction for your domain; influencing standards and architectural decisions across teams through credibility and collaboration; and shipping multiple large services, shared libraries, or major infrastructure improvements.
Zeta Global is a data-powered marketing technology company founded in 2007 and publicly traded on the NYSE (ZETA). The company combines the industry's 3rd largest proprietary data set (2.4B+ identities) with AI to unlock consumer intent and personalize experiences. The Zeta Marketing Platform (ZMP) unifies customer data, identity, and advanced analytics, and the company is advancing this with Athena by Zeta™, a superintelligent conversational agent that personalizes the marketer's workspace and recommends next-best actions.
REQUIREMENTS:
- 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, including 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 (Cursor, GitHub Copilot) and comfort with "vibe coding"–style workflows that favor fast iteration, tight feedback loops, and continuous refactoring
- Proficiency in one or more backend languages commonly used for large-scale systems (Python, Java, Go, Scala)
- Bachelor's or master's degree in computer science, mathematics, or a related field, or equivalent practical experience
