AI Ops Application Operations Lead at Zeta Global | AdTechTalent
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Zeta Global
AI Ops Application Operations Lead
AI Opsapplication operationstechnical program managementproduct managementproduction readinessrelease managementfeedback loopsapplication lifecycledashboardsmetricsagentic codingAI-assisted developmentlow-codeworkflow automationsecurityprivacydata accessmonitoringdocumentationstakeholder coordination
Key details
Salary
Not specified
Employment type
Full-time
Seniority
Lead
Years experience
5-10
Location
Hyderabad, India
Full job description
Lead the production lifecycle of agentic coding applications, plugins, and skills. Partner with application owners and technical teams to ensure production readiness, lifecycle and release management, and application reliability. Manage operational health, coordinate updates, and maintain documentation. Establish feedback loops, translate user feedback into product requirements, and support prioritization. Develop dashboards and define metrics to monitor adoption, performance, and business impact. Apply AI Ops standards, create reusable templates, and support governed application portfolio management. Requires experience in application operations, technical program management, product management, backlog and release management, and performance metrics. Preferred experience with AI-assisted development, AI models, APIs, security, privacy, analytics, and software development practices.
What you'll do
Partner with owners of agenticly coded applications to assess production readiness
Establish and manage production-readiness process covering security, privacy, data access, architecture, user experience, support, monitoring, and documentation
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Ensure applications have clear business objectives, target users, success measures, and accountable owners before launch
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Help establish structured feedback loops with users
Collect and organize user feedback, feature requests, defects, and usage insights
Translate feedback into clear product requirements and backlog items
Support prioritization of improvements based on user value, business impact, risk, and effort
Coordinate user testing and validation before major releases
Identify common patterns for shared standards, reusable components, or broader AI Ops priorities
Develop and maintain dashboards for adoption, usage, reliability, performance, and business outcomes
Define appropriate metrics for each application including active users, usage frequency, task completion, response quality, errors, latency, user satisfaction, and estimated time or cost savings
Monitor application health and surface risks, adoption gaps, and improvement opportunities
Partner with application owners to review performance regularly and agree on actions
Help determine whether applications should be expanded, redesigned, consolidated, or retired
Apply AI Ops standards for development, production readiness, responsible AI, security, documentation, and measurement
Create reusable templates, checklists, playbooks, and operating procedures
Support development of governed application portfolio and inventory
Ensure clear ownership, approved data access, defined user groups, and appropriate controls
Promote consistency across applications while allowing teams to move quickly and iterate
Requirements
Experience in application operations, technical program management, product operations, product management, or a 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 a fast-moving environment with evolving tools, standards, and priorities
Preferred: Experience with AI-assisted software development, low-code tools, or agentic coding platforms
Preferred: Familiarity with modern AI models, APIs, agents, workflow automation, and application architectures
Preferred: Experience working with enterprise security, privacy, identity, access management, and software governance processes
Preferred: Familiarity with analytics tools, application monitoring, user telemetry, and experimentation
Preferred: Experience supporting internal enterprise applications or employee productivity tools
Preferred: Working knowledge of software development practices, including testing, deployment, version control, and incident management
Tech stack
AI-assisted development toolsAI modelsAPIsagentic coding platformslow-code toolsworkflow automationapplication monitoringanalytics toolssoftware development practicestestingdeploymentversion controlincident management
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