Senior Agentic AI Engineer

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 . Role Snapshot We’re hiring a hands-on Agentic AI engineer to build bidder-adjacent agents that improve campaign performance using RAG + tool-using workflows in a closed-loop ACE (Observe → Reason → Act → Evaluate) . This is not a classic “train a model and deploy it” role—this is agentic decisioning + evaluation + safety in a low-latency AdTech environment. What You’ll Do Build bidder-adjacent agentic workflows that recommend/execute campaign control actions (targeting constraints, budget pacing levers, bid modifiers, supply/inventory selection , creative routing). Implement production-grade RAG: retrieval from policies/playbooks, campaign history, aggregates, and near-real-time telemetry; optimize grounding and reduce hallucinations. Create safe tool/action interfaces: idempotent execution, audit logs, dry-run + approval gates, rate limits, rollback/fallback behaviors. Own AgentOps : eval harnesses, regression suites, online experimentation (A/B), metrics tied to outcomes (CPA/ROAS, pacing, quality, margin). Add observability end-to-end (tracing prompts/retrieval/tool calls/latency) and reliability patterns (timeouts, circuit breakers, safe defaults). Partner with Backend/Bidding, Data Platform, DS/Optimization, Product, and SRE to define the boundary between deterministic per-request bidding and agent-driven control-plane decisions. Must-Have Qualifications 5+ years building production backend and/or applied AI systems (design → ship → operate ). Strong engineering in Java or Go (Python OK for evals/tooling). Hands-on experience with LLMs and agentic patterns (tool use, structured outputs, multi-step loops). Hands-on RAG experience (embeddings, hybrid retrieval, reranking, chunking, context assembly). Experience building evals and monitoring for AI systems (offline benchmarks + online experiments). Cloud + distributed systems fundamentals (APIs, microservices, streaming/ eventing ; AWS preferred). Nice-to-Have Programmatic advertising (DSP/SSP/RTB) or other high-scale real-time decisioning domains. Experience with safety/policy enforcement for agent tools (prompt/tool sanitization, allowlists, schema validation). Experience designing “AI control plane” systems that influence production outcomes while keeping serving paths stable. Familiarity with experimentation platforms, feature stores, and large-scale telemetry pipelines. Keywords (for sourcing) Agentic AI, RAG, LLM tool use, bid optimization, pacing, targeting, control plane, evals, observability, RTB/DSP, Java/Go, AWS, streaming telemetry BENEFITS PERKS Unlimited PTO Excellent medical, dental, and vision coverage Employee Equity Employee Discounts, Virtual Wellness Classes, and Pet Insurance And more!! SALARY RANGE The salary range for this role is $150,000 - $180,000, depending on location and experience. PEOPLE CULTURE AT ZETA Zeta considers applicants for employment without regard to, and does not discriminate on the basis of an individual’s sex, race, color, religion, age, disability, status as a veteran, or national or ethnic origin; nor does Zeta d ... (truncated, view full listing at source)