Senior Manager, Agentic AI

Role Overview

The Sr. Manager, Agentic AI is part of the CLOUDx Engineering organization and serves the existing Agentic AI team. The core objective is to build and scale agentic AI capabilities that improve the experience and productivity of CLOUDx customers and engineers by reducing IRIS ticket volumes, accelerating time-to-fulfillment, and expanding self‑service for common cloud requests and operational workflows. The role will define the product and engineering roadmap for agentic solutions across CLOUDx services, lead a team of engineers (direct reports) to deliver production‑grade capabilities, and partner closely with CLOUDx service owners, operations teams, and strategic managed‑service partners to drive adoption and measurable outcomes.

• Lead and develop a high‑performing Agentic AI engineering team, including hiring, coaching, performance development, and succession planning.
• Own the strategy, roadmap, and prioritized delivery backlog for Agentic AI capabilities that measurably reduce IRIS ticket volumes, improve end‑user experience, and expand CLOUDx self‑service.
• Partner with CLOUDx service owners, network, security, risk & compliance, and managed‑service partners to identify high‑value use cases and drive adoption at scale.
• Architect and guide implementation of agentic solutions using Amazon Bedrock and other J&J‑approved platforms, including tool/function calling, workflow orchestration, and integration with enterprise systems (ticketing, CMDB, service catalog, monitoring/observability, knowledge bases).
• Establish engineering standards for production‑grade agents (reliability, latency, cost, testing, release management), and ensure scalable, API‑first designs aligned to CLOUDx platform architecture.
• Define and implement agent safety and governance patterns, including access controls, approvals, human‑in‑the‑loop workflows, audit logging, prompt/tool security, and policy‑compliant data handling.
• Drive an outcomes‑based operating model with clear KPIs (ticket deflection, IRIS reduction, MTTR, containment rate, CSAT, hours saved, cost‑to‑serve) and report progress to CLOUDx and stakeholder leadership.
• Lead delivery execution across discovery, prototyping, pilots, and production rollout; manage dependencies, risks, and change management required for enterprise adoption.
• Own relationships and technical direction with strategic vendors/partners supporting CLOUDx services and AI enablement; ensure quality, security, and contractual outcomes are met.
• Champion continuous improvement by analyzing IRIS themes and operational telemetry to prioritize automation and agentic opportunities, expanding self‑healing and self‑service over time.

• Minimum of a Bachelor’s degree in Computer Science, Engineering, or a related discipline.
• 10+ years of experience in software engineering, platform engineering, cloud automation, or SRE, including leading delivery of enterprise‑grade services.
• 3+ years of people‑management experience, including hiring, coaching, performance management, and building high‑performing engineering teams.
• Demonstrated experience designing and delivering agentic AI / LLM‑enabled solutions in production, including orchestration, tool integration, and operationalization.
• Strong software engineering fundamentals with hands‑on ability in modern programming (Python strongly preferred) and API‑first/microservices architectures.
• Experience integrating AI/automation with service management and operations systems (ticketing workflows, service catalog, knowledge management, CMDB, observability platforms).
• Practical experience with Infrastructure‑as‑Code and CI/CD (e.g., Terraform, pipelines) and applying SRE/operational excellence practices to reduce MTTR and cost‑to‑serve.
• Deep understanding of enterprise security, risk, compliance, identity/credential handling, and auditability required for autonomous or semi‑autonomous actions.
• Strong stakeholder management and executive communication skills, with a track record of driving cross‑functional alignment and measurable outcomes.

• Hands‑on experience with Amazon Bedrock and common agent patterns…