Staff Software Engineer - Performance Advisor

Zeta Global is hiring a hands-on Staff Software Engineer to provide technical leadership for its Forecasting and Recommendations platforms, with a focus on production-grade AI and agentic systems. The role designs, builds, and operates high-throughput, low-latency distributed systems, while owning reliability, observability, and operational excellence.

Responsibilities:

• 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 withfoundational LLMs (e.g., GPT, Claude, Gemini Pro), selecting appropriate models and deployment patterns based on latency, cost, and reliability tradeoffs
• Use frameworks and tooling such as LangChain, voice agents, and related ecosystems to accelerate development—while enforcing production discipline
• Embrace AI-assisted development workflows (e.g., Cursor, GitHub Copilot, vibe coding paradigms) to move quickly without sacrificing quality
• 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

Requirements:

• 12+ years of professional software engineering experience building and operating production-grade distributed systems
• A 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 (e.g., Cursor, GitHub Copilot) and comfort working in “vibe coding”–style workflows that favor fast iteration, tight feedback loops, and continuous refactoring
• 2+ years of experience in Python and proficiency in one or more backend languages commonly used for large-scale systems (e.g., Python, Java, Go, Scala)
• Bachelor's or master's degree in computer science, Mathematics, or a related field, or equivalent practical experience