About this role
The AI Ops Application Operations Lead manages the production lifecycle of agentic coding applications, plugins, and skills at Zeta Global. The role helps application owners move high-value prototypes into production and keeps launched applications reliable, governed, useful, and measurable. It works across AI Operations, business, product, engineering, IT, Security, Data, and other teams; the lead need not be the primary developer of every application.
Responsibilities
- Assess prototypes for production readiness across security, privacy, data access, architecture, user experience, support, monitoring, and documentation. Identify launch risks and dependencies; coordinate approvals and deployment; and create launch plans, checklists, support models, and ownership records. Confirm business objectives, target users, success measures, and accountable owners before launch.
- Manage operational health and a prioritized backlog of fixes and enhancements. Coordinate testing, releases, and user communications; maintain documentation and escalation paths; and address compatibility with changing models, APIs, enterprise systems, data sources, and security requirements.
- Establish user-feedback loops, turn requests and usage insights into requirements, support prioritization and user validation, and identify opportunities for shared standards and reusable components.
- Build or maintain dashboards covering adoption, usage, reliability, performance, and business outcomes. Define measures such as active users, task completion, response quality, errors, latency, satisfaction, and estimated time or cost savings. Use evidence to recommend whether applications should expand, be redesigned, be consolidated, or be retired.
- Apply AI Ops, responsible AI, security, and documentation standards; develop reusable playbooks and procedures; and maintain a governed application inventory with defined ownership, approved data access, user groups, and controls.
Required qualifications
Experience in application operations, technical program management, product operations, product management, or a related role, including taking internal digital products, AI applications, or technology solutions from prototype to production. Candidates need cross-functional coordination, business-to-technical requirements translation, backlog prioritization, documentation, release management, product metrics and dashboards, strong communication, and comfort with evolving priorities. No number of years or degree requirement is stated.
Preferred
AI-assisted development, low-code or agentic coding platforms; familiarity with AI models, APIs, agents, automation, and application architecture; enterprise security, privacy, identity and access management, and governance; analytics, monitoring, telemetry, and experimentation; internal enterprise or employee-productivity applications; and software testing, deployment, version control, and incident management. Success is measured by faster, more reliable launches, clear ownership and support, visibility into impact, responsiveness to feedback, and sustained adoption.