Position SummaryThe Senior Director, Agentic Service Experience is responsible for standing up, leading, and scaling McKesson's Agentic Service Experience function, serving as the product owner for Sierra AI agents across NAPS contact center customers. Initial scope is supporting Customer Experience Operations. This role defines the vision, strategy, and execution approach for this new function that both runs and continuously improves AI-powered service capabilities across email, chat, and voice.
The leader oversees and integrates four core capability areas-Product Management, Process & Journey Engineering, Agent Tuning & Knowledge Architecture, and AI Performance & Quality Analysis-ensuring they operate as a cohesive system to deliver measurable business and customer outcomes. This role is accountable for building the function from the ground up, leading leaders across multiple teams, and aligning enterprise priorities to coordinated, cross-capability execution.
The role owns end-to-end performance of the agent product and function, defines and prioritizes the improvement backlog, drives release and change control decisions, and holds Sierra and McKesson Technology accountable for delivery. Sitting close to the customer, this leader integrates work across teams to deliver containment, accuracy, and customer experience outcomes, while building, developing, and scaling the team and function through FY27 and beyond.
Key ResponsibilitiesAgentic Service Experience Team Leadership- Lead multiple interdependent Agentic capability areas, ensuring alignment across Product Management, Performance & Quality, Knowledge Architecture, and Process Engineering
- Direct and develop first- and second-line leaders, establishing clear accountability for each capability area while driving integrated outcomes
- Set and evolve the operating model for Agentic services, ensuring consistency in delivery, governance, and performance across all teams
- Act as the single accountable leader for end-to-end Agentic outcomes, balancing competing priorities across functions and driving enterprise-level decisions
AI Service Business Ownership- Serve as the owner for Agentic service performance and outcomes across NAPS CxO contact centers to start. Role is designed to grow in scope as technology advances.
- Represent agentic service to CxO and NAPS leadership. Provide credible, data-driven narratives on what agents are doing, what they are producing, and what needs investment or change. Make agent performance legible to non-AI audiences.
- Own the senior business relationship with Sierra. Hold the vendor accountable for performance commitments and roadmap delivery at the senior level. Use CxO's proximity to the customer to shape what Sierra builds.
- Serve as CxO's senior counterpart to McKesson Technology (MT) and Contact Center Technology Solutions (CCTS) on agent-related decisions. MT/CCTS own the underlying platform stack; this role owns the agent product that runs on it.
- Establish pillar governance and operating standards. Document how the capability runs: how new use cases get approved, how performance is reported, how issues are escalated, how releases happen. Make the operating model legible to anyone joining or auditing it.
Agent Product Ownership- Own the integrated agentic roadmap across all capability areas, ensuring prioritization reflects enterprise value, operational impact, and risk
- Balance trade-offs across multiple teams and investments, ensuring cohesive execution rather than siloed optimization
- Own day-to-day AI agent performance. Monitor containment, accuracy, latency, escalation quality, and customer sentiment across channels and customer groups. Drive corrective action when performance drifts.
- Define and maintain the agent improvement roadmap and backlog. Prioritize intents, use cases, and capability enhancements informed by performance data, frontline feedback, and QA findings. Sequence releases against operational readiness and risk.
- Translate signals into product changes. Convert observed errors, customer complaints, and edge cases into prioritized fixes. Close the loop back to operators on what changed and why.
Cross-Functional Solution Design- Define the end-to-end agent workflow. Ensure each new agent capability aligns with McKesson standards, policy guardrails, and risk appetite. Work with the Process & Journey Engineer to ensure each capability fits into the broader customer journey.
- Own the human-AI handoff design with the Process & Journey Engineer. Define what context, intent, and prior steps transfer when the agent escalates to a representative. The way work gets done across human and AI cannot be bifurcated.
- Optimize the AI tool interface for representatives and SMEs. Ensure agent-assist surfaces, intent context, and recommended actions are usable, accurate, and trusted by frontline teams.
Governance, Risk, and Change Control- Own governance for the Agentic service function, ensuring consistent standards across all capability areas
- Define AI guardrails and escalation criteria in partnership with the AI Performance & Quality Analyst and Responsible AI partners. Ensure agents operate within risk and compliance boundaries.
- Own change control for agent releases. Establish go / no-go criteria, fallback protocols, and post-launch monitoring for each new capability. Document decisions and rationale.
- Report agent performance to CxO and NAPS leadership. Surface agent performance, release activity, and roadmap status to the VP of CxO and broader NAPS leadership on a regular cadence, including risks and decisions that require leader attention.
Budget & Investment Management- Own and manage the full Agentic service function budget across people, external services, and AI-related investments
- Establish and maintain a clear view of AI investment vs. business outcomes
- Lead annual planning and in-year budget governance, ensuring disciplined investment decisions aligned to NAPS priorities
Team Leadership & Development - Lead, coach, and develop the Agentic Service Experience team
- Set performance expectations, priorities, and operating cadence
- Build capability in AI product management, analytics, and operational excellence
- Drive a high-performance, outcomes-oriented team culture aligned to NAPS priorities
Minimum RequirementDegree or equivalent experience. Typically requires 13+ years of professional experience and 6+ years of diversified leadership, planning, communication, organization, and people motivation skills (or equivalent experience).
EducationMBA or equivalent advanced degree.
Critical Skills- 13+ years of professional experience, including 7+ years of product management experience, and 3+ years owning AI, conversational AI, automation, or contact center technology products in a customer-facing operational context.
- 6+ years of experience leading teams or managing people in a product, operations, or technology environment.
- Demonstrated ownership of a product or capability where success was measured in operational outcomes (containment, deflection, automation rate, resolution accuracy, customer satisfaction at handoff) rather than feature delivery alone.
- Hands-on experience with at least one conversational or agentic AI platform deployed at enterprise scale (e.g., Sierra, Salesforce Agentforce, Google CCAI, Amazon Lex, Cognigy, Ada, Intercom Fin, Kore.ai).
- Experience translating frontline, QA, and customer feedback into a prioritized product backlog and shipping improvements on a regular release cadence.
- Working fluency in AI / ML concepts relevant to deployed agents: prompt design, intent modeling, model evaluation, human-in-the-loop systems, guardrails, model drift, and observability.
- Strong cross-functional collaboration skills with the ability to partner credibly with engineering, operations, QA, frontline supervisors, and senior business leaders.
- Analytical fluency: comfortable defining metrics, instrumenting performance dashboards, interpreting data, and making evidence-based prioritization decisions.
- Demonstrated judgment in ambiguous, fast-moving environments where requirements evolve as the product learns.
Preferred Qualifications- Direct experience with the Sierra platform or a comparable agentic AI platform deployed at enterprise scale.
- Contact center, customer service, or BPO domain experience, particularly in healthcare, life sciences, or regulated industries.
- Experience operating in a multi-channel environment (email, chat, voice) with awareness of the operational and design differences across channels.
- Familiarity with responsible AI principles, AI governance frameworks, and risk and compliance considerations for AI deployed in regulated customer interactions.
- Experience working alongside or in partnership with management consulting firms or transformation programs.
This is a hybrid role based in our Fort Worth office. While remote work is available, the selected candidate will be required to travel to and work on-site in Fort Worth approximately once per month.
We are proud to offer a competitive compensation package at McKesson as part of our Total Rewards. This is determined by several factors, including performance, experience and skills, equity, regular job market evaluations, and geographical markets. The pay range shown below is aligned with McKesson's pay philosophy, and pay will always be compliant with any applicable regulations. In addition to base pay, other compensation, such as an annual bonus or long-term incentive opportunities may be offered. For more information regarding benefits at McKesson, please click here.
Our Base Pay Range for this position$168,500 - $280,900
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