Zeta Global

Principal Product Manager

Zeta Global • $185K — $205K *
Atlanta, GA 30349In-Person
Information Technology
Less than 5 years of experience
Today
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Job Overview by Ladders

Qualifications

  • 5+ years of product management experience with complex technical products involving LLMs and AI agents.
  • Expertise in agentic systems, workflows, and state management.
  • Experience designing or working with context and knowledge architectures such as context graphs.
  • Strong understanding of telemetry and observability for AI systems.
  • Exceptional ability to align cross-functional teams and influence senior stakeholders.
  • Technical proficiency with tools like LangSmith and experience in modern AI development environments.
  • Demonstrated problem-solving skills with a knack for rapid prototyping.

Responsibilities

  • Develop and manage architecture for chaining LLM agents and workflows across complex use cases.
  • Lead the creation of a shared Context Graph for persistent user awareness.
  • Implement context streaming services for real-time agent awareness.
  • Define telemetry frameworks to analyze agent operations in production.
  • Build robust evaluation frameworks for agent quality and reliability.
  • Lead the development of a Model Workbench for non-technical users to leverage AI safely.
  • Drive alignment among cross-functional teams around agent architecture and platform standards.

Benefits

  • Unlimited PTO
  • Excellent medical, dental, and vision coverage
  • Employee equity
  • Employee discounts and virtual wellness classes
  • Pet insurance
Full Job Description
Role Responsibilities
  • Agent Chaining and Orchestration: Develop and manage the architecture for chaining LLM agents, tools, models, and workflows across complex use cases. Ensure seamless orchestration, handoffs, state management, and integration across the platform.
  • Context Graph and Context Architecture: Lead the development of a shared Context Graph that gives agents persistent awareness of users, brands, accounts, workflows, capabilities, data, prior actions, goals, and outcomes. Define how context is captured, structured, retrieved, governed, and made available across agents and products.
  • Context Streaming Services: Implement and manage context streaming services that provide agents with real-time awareness of user actions, application state, system events, and relevant business data. Ensure context remains current, permission-aware, and usable across multi-step workflows.
  • Agent Telemetry and Observability: Define the telemetry framework required to understand how agents operate in production. Instrument and analyze intent routing, agent and tool selection, context utilization, handoffs, latency, errors, completion rates, confidence, user interventions, and business outcomes. Build the feedback loops necessary to continuously improve agent performance.
  • Agent Evaluation Suites: Build robust evaluation frameworks for testing agent quality, reliability, routing, context utilization, tool execution, and end-to-end workflow completion. Establish both offline and production evaluation methodologies that enable measurable improvements over time.
  • Model Workbench Development: Lead the creation of a Model Workbench designed for marketers and other non-technical users, enabling them to safely leverage LLMs, traditional ML, agents, and workflows without requiring deep technical expertise.
  • MCP Capability and Tool Registry: Oversee the registration, documentation, governance, and discoverability of Model Context Protocol servers, tools, agents, and platform capabilities. Ensure capabilities are easy for both developers and agents to understand, select, and invoke correctly.
  • Cross-Functional Architecture and Organizational Alignment: Drive alignment across Product, Engineering, Data Science, Design, Analytics, Security, and business stakeholders around shared agentic architecture, context standards, ownership models, evaluation criteria, and platform priorities. Establish clear accountability and operating models for capabilities that span multiple teams.
  • Platform Standards and Governance: Define standards for how agents, tools, context sources, telemetry, and workflows are built and integrated across the organization. Balance local team autonomy with the consistency required to create a coherent platform experience.
  • Technical Troubleshooting and Prototyping: Actively participate in troubleshooting and debugging using tools such as LangSmith and related observability platforms. Lead by example by rapidly building proof-of-concepts to validate technical approaches, identify architectural constraints, and demonstrate new product opportunities.
  • Advocacy for Rapid Iteration: Promote a culture of rapid prototyping, experimentation, and evidence-based iteration. Use lightweight development and "vibe coding" where appropriate to quickly turn ideas into working experiences before investing in production-scale implementations.
Required Qualifications
  • Product Management Experience: Demonstrated experience leading complex technical products, particularly those involving LLMs, AI agents, workflow systems, developer platforms, ML infrastructure, or AI-driven applications.
  • Agentic Systems Expertise: Strong understanding of LLM agents, tool use, orchestration, multi-agent workflows, state management, context management, and the architectural patterns required to operate agentic systems reliably at scale.
  • Context and Knowledge Architecture: Experience designing or working with context graphs, knowledge graphs, semantic systems, memory architectures, metadata platforms, or other systems that allow applications and models to understand relationships between users, data, actions, and business objects.
  • Telemetry and Observability: Strong understanding of instrumentation, telemetry, evaluation, and observability for complex software or AI systems. Ability to define the signals required to distinguish between model failures, orchestration failures, context failures, tool failures, and UX failures.
  • Organizational Alignment and Influence: Exceptional ability to align senior stakeholders and cross-functional teams around shared technical architecture, product priorities, ownership boundaries, and operating standards. Comfortable leading initiatives where no single team controls the entire outcome.
  • Systems Thinking: Ability to reason across product experience, model behavior, data, infrastructure, APIs, organizational ownership, and operational processes rather than optimizing individual components in isolation.
  • Technical Proficiency: Strong technical background with hands-on familiarity with tools such as LangSmith and experience working with APIs, workflow orchestration, LLM agent chaining, MCP, evaluation frameworks, and modern AI development environments.
  • Problem-Solving and Prototyping: Demonstrated ability to troubleshoot ambiguous technical problems, rapidly prototype potential solutions, and translate experimentation into scalable product and architectural decisions.
  • Communication and Collaboration: Excellent communication skills with the ability to translate highly technical concepts into clear product strategies, operating models, and decisions for technical and non-technical audiences.
Preferred Qualifications
  • Experience building or operating agentic infrastructure, AI platforms, context platforms, knowledge graphs, or developer ecosystems.
  • Experience integrating traditional machine learning with generative models and agentic systems, including using predictive models as tools or contextual inputs for agents.
  • Experience with workflow orchestration platforms and distributed systems involving multiple services, teams, and execution environments.
  • Experience designing AI telemetry, evaluation systems, experimentation frameworks, or production observability for LLM-powered products.
  • Demonstrated success establishing cross-functional technical standards and governance across multiple engineering and product organizations.
  • Experience building systems where context, telemetry, and evaluation form a continuous learning loop, allowing agent behavior and product experiences to improve based on real-world usage.

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 $185,000 - $205,000, depending on location and experience.

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About Zeta Global

Zeta Global is a data-driven marketing technology company that combines the power of artificial intelligence with the scale of data, applying insights from over 2.4 billion user profiles to generate business outcomes. Zeta Global?s products and services include programmatic media buying, email marketing, CRM, data and analytics, and marketing automation. The company serves a wide range of industries, including financial services, insurance, automotive, telecommunications, retail, publishing, and travel. Zeta Global has offices in North America, Europe, and Asia-Pacific.
Learn more about Zeta Global
Size
1,300 employees
Market Cap
$1.7 billion
Industry
Media
Founded
2007
NASDAQ
ZETA
* Ladders Estimates

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