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Zeta Global seeks an AI Ops Application Operations Lead to own the production lifecycle of agentic coding applications, plugins, and skills across the organization. This role bridges application owners, AI Operations, IT, Security, and technical teams to move high-value prototypes into production while ensuring applications remain reliable, governed, and measurable post-launch.
Key Responsibilities:
Production Readiness & Launch: Partner with application owners to assess production readiness. Establish and manage a consistent production-readiness process covering security, privacy, data access, architecture, UX, support, monitoring, and documentation. Identify launch risks and dependencies, coordinate cross-functional work, and develop launch plans, readiness checklists, and ownership documentation. Ensure applications have clear business objectives, target users, success measures, and accountable owners.
Application Operations & Lifecycle Management: Manage ongoing operational health of production applications. Maintain prioritized backlogs of fixes and enhancements. Coordinate updates, testing, release management, and user communication. Ensure compatibility with model, API, and security changes. Establish escalation paths for defects, incidents, and performance concerns. Maintain accurate documentation for functionality, dependencies, ownership, and support procedures.
Feedback, Adoption & Continuous Improvement: Help establish structured user feedback loops. Collect and organize feedback, feature requests, defects, and usage insights. Translate feedback into clear product requirements and backlog items. Support prioritization based on user value, business impact, risk, and effort. Coordinate user testing before major releases. Identify patterns across applications to inform shared standards and reusable components.
Measurement & Analytics: Develop and maintain dashboards providing visibility into adoption, usage, reliability, performance, and business outcomes. Define appropriate metrics (active users, usage frequency, task completion, response quality, errors, latency, satisfaction, estimated savings). Monitor application health and surface risks. Partner with owners on regular performance reviews. Help determine whether applications should be expanded, redesigned, consolidated, or retired.
Governance, Standards & Portfolio Management: Apply AI Ops standards for development, production readiness, responsible AI, security, and documentation. Create reusable templates, checklists, and playbooks. Support development of a governed application portfolio and inventory. Ensure clear ownership, approved data access, defined user groups, and appropriate controls. Promote consistency while enabling teams to move quickly.
Success Metrics: Increased percentage of prototypes moved to production, reduced time from prototype to launch, stronger production readiness with fewer post-launch issues, clear ownership and support models for all production applications, consistent visibility into adoption and impact, faster response to feedback and issues, increased adoption and sustained usage, and a well-managed portfolio aligned to business priorities.
Role Profile: Well-suited for someone who enjoys turning early-stage prototypes into dependable, scalable applications. Comfortable operating between business and technology teams, creating structure in developing processes, and helping owners make decisions based on user feedback and performance data. Practical, organized, technically curious, and focused on measurable outcomes. Knows when to move quickly and when to address risk, keeping teams aligned throughout the lifecycle.
Requirements:
Required:
- Experience in application operations, technical program management, product operations, product management, or closely related role
- Strong ability to coordinate work across business, product, engineering, IT, security, and data teams
- Experience taking internal digital products, AI applications, or technology solutions from prototype through production launch
- Ability to translate business requirements into clear technical and operational requirements
- Strong backlog management, prioritization, documentation, and release management skills
- Experience defining product metrics and building or managing performance dashboards
- Strong written and verbal communication skills
- Comfort working in fast-moving environment with evolving tools, standards, and priorities
Preferred:
- Experience with AI-assisted software development, low-code tools, or agentic coding platforms
- Familiarity with modern AI models, APIs, agents, workflow automation, and application architectures
- Experience with enterprise security, privacy, identity, access management, and software governance processes
- Familiarity with analytics tools, application monitoring, user telemetry, and experimentation
- Experience supporting internal enterprise applications or employee productivity tools
- Working knowledge of software development practices including testing, deployment, version control, and incident management
