Senior Manager Information Systems (Services IT)

Zebra Technologies•Holtsville, NY

2d•$138,800 - $208,200•Hybrid

About The Position

The Senior Manager : Services IT Applications will need to be proficient with Salesforce Service Cloud and will lead the strategy, architecture, and delivery of next-generation customer service experiences powered by Salesforce Service Cloud, AgentForce, and the broader Salesforce AI ecosystem. This role requires deep expertise in Service Cloud, autonomous AI agents, generative AI, and enterprise-scale platform design. The ideal candidate will drive the adoption of AI-first service strategies, architect intelligent automation solutions using AgentForce, and ensure the Salesforce platform delivers scalable, secure, and high-performance outcomes aligned with business objectives.

Requirements

Bachelor’s Degree required.
Minimum 12+ years of experience in IT or equivalent discipline with at least 5 years of management experience.
Minimum of 10+ years of Salesforce

Nice To Haves

Advanced Degree preferred.
Salesforce Agentforce
Ability to manage leaders of others
Experience managing budgets
Ability to apply strategic concepts for process improvement
Demonstrate regular interactions with Senior management or executive levels on matters concerning several functional areas, business units, and/or Customers
Experience with technical and leadership skill

Responsibilities

Own the end-to-end architecture, design, and roadmap for Salesforce Service Cloud, including Omni-Channel, Case Management, Knowledge, Entitlements, Milestones, Service Console, and Field Service Lightning
Lead the design and implementation of AgentForce autonomous AI agents, defining agent topics, actions, guardrails, and escalation patterns to automate customer service workflows at enterprise scale
Architect AI-first service experiences leveraging Einstein AI, Einstein Copilot, Prompt Builder, Einstein Bots, and AgentForce to deflect cases accelerate resolution and enhance agent productivity.
Design and deploy intelligent routing, sentiment analysis, next-best-action recommendations, and predictive service models to transform the customer service lifecycle.
Drive the integration of Data Cloud with Service Cloud to create unified customer profiles, enabling real-time personalization and AI-driven insights across all service touchpoints.
Architect scalable solutions that span Service Cloud, Sales Cloud, Experience Cloud, Marketing Cloud, Manufacturing Cloud, and Data Cloud where cross-cloud capabilities are required.
Lead design of digital experience sites, self-service portals, and community platforms with embedded AI-powered search, chatbots, and autonomous agent experiences.
Provide architectural oversight for high-complexity projects involving custom development, API integrations, and multi-cloud capabilities
Define and enforce platform implementation standards, technical documentation, and architectural best practices.
Serve as the organizational subject matter expert on AgentForce, guiding business teams on where autonomous agents can replace or augment traditional service workflows.
Design agent orchestration patterns including multi-agent coordination, human-in-the-loop escalation, and feedback loops for continuous agent improvement.
Establish governance frameworks for AI agent deployment, including testing strategies, guardrail configuration, prompt management, and hallucination mitigation.
Evaluate and integrate emerging Salesforce AI capabilities (Einstein Trust Layer, grounding, retrieval-augmented generation) into the service architecture.
Build proof-of-concepts and prototypes to demonstrate AI-driven service transformation opportunities to executive leadership.
Conduct internal and external Salesforce security risk assessments and implement mitigation strategies, with particular focus on AI data privacy and ethical AI use.
Oversee platform security posture including identity, access management, governance policies, and data protection practices.
Define security and compliance standards for AI agent interactions, ensuring customer data handling meets regulatory requirements and the Einstein Trust Layer is properly configured.
Ensure adherence to compliance frameworks and support audit activities as needed.
Establish DevOps standards using tools such as Flosum, code scanners, and OwnBackup to ensure high-quality, secure, and reliable deployments.
Define CI/CD practices and enforce release governance across multiple development teams.
Implement testing and deployment standards specific to AI components, including agent behavior validation, prompt regression testing, and performance benchmarking.
Build and mentor strong cross-functional teams, collaborating closely with product owners, business stakeholders, contact center leadership, engineering groups, and executive leadership.
Partner with customer experience and contact center teams to translate service KPIs (CSAT, FCR, AHT, deflection rates) into architectural decisions and AI-driven solutions.
Present architectural recommendations, AI adoption roadmaps, and cross-functional project proposals to senior management and business units.
Facilitate alignment between technical capabilities and evolving business strategies, championing an AI-first mindset across the organization.
Develop strategic plans, cost estimates, budgets, and schedules for Service Cloud enhancements, AI implementations, and new AgentForce deployments.
Manage full lifecycle delivery of large-scale Salesforce projects using both Scrum and Kanban frameworks.
Build and maintain Confluence documentation, Jira boards, and project workflows.
Lead ongoing assessment of service platforms, AI agent performance, and infrastructure, providing recommendations to improve performance, scalability, and efficiency.
Analyze complex customer service challenges and identify opportunities for automation and AI-driven resolution through Salesforce solutions.
Partner with internal and external stakeholders, applying a strong understanding of current industry trends in conversational AI, autonomous agents, and Salesforce innovations.
Guide teams in evaluating, selecting, and implementing solutions that are cost-effective and meet user, organizational, and customer experience requirements.
Define and track AI adoption metrics, including agent deflection rates, autonomous resolution rates, and time-to-resolution improvements.