Consulting Managed Services AI, IT and Automation Senior Manager

Managed Services AI IT & Automation Architect Senior Manager

EY is seeking a clientfacingManaged Services AI IT & Automation Architect (Senior Manager)to design operationalize and scale AIenabled managed services for our clients. This role is accountable for orchestrating the endtoend tooling strategy across AI automation cloud ITSM and observability and for creating a compelling reusable framework that enables clients to move from experimentation to enterprisegrade productionready managed services.

The Senior Manager will balance handson architecture leadership with client advisory and delivery oversight ensuring services are resilient secure compliant and measurable through clear SLAs SLOs and value outcomes.

The Opportunity

• Orchestrate the tooling story:Bring together AI/ML platforms automation technologiesDevSecOps ITSM and observability into a coherent supportable managed services ecosystem.
• Create a compelling framework:Define a practical repeatableAIled Managed Services Frameworkthat clients can adopt to scale with confidence governance and cost transparency.

Your Key Responsibilities

• Client Advisory & Value Design
  • Lead client discovery sessions platform assessments and tooling rationalization workshops across AI automation and IT operations.
  • Translate businessobjectivesinto managed service architectures platform roadmaps and operating models.
  • Develop business cases (TCO/ROI) and outcomebased value narratives tied to cost reduction resiliency speed and risk mitigation.
  • Present executivelevel recommendations explaining tooling choices tradeoffs and longterm sustainability.
• Reference Architecture & Framework Development
  • Design document and evolve EYs AILed Managed Services Framework covering:
    • Strategy & Value: outcomes KPIs funding and consumption models
    • Process & ITIL v4: Incident Problem Change Request Knowledge CMDB
    • Platform & Integration: cloud landing zones APIs eventdriven patterns
    • AI & Automation: GenAI LLM/RAG patternsMLOps RPA/ITPA orchestration
    • Security & Risk: identity data protection Responsible AI guardrails
    • SRE & Observability: SLOs/SLIs error budgets runbooks autoremediation
    • FinOps: unit economics cost optimization capacity management
  • Produce reference architectures decision matrices control catalogs and reusable accelerators.
• Platform & Tooling Orchestration
  • Architect and integrate endtoend toolchains spanning:
    • Cloud &DevSecOps: Azure (preferred) AWS GCP; Kubernetes; Terraform; GitHub/Azure DevOps;GitOps
    • Data & AI: Azure OpenAI Databricks Snowflake vector databasesMLOpspipelines prompt/version management
    • Automation: UiPath Power Automate Azure Automation eventdriven workflows
    • ITSM & AIOps: ServiceNow Jira Service Management Dynatrace Azure Monitor Prometheus/Grafana
    • Security: Entra ID Key Vault Sentinel/Splunk DLP and data governance tools
    • Ensure interoperability scalability and operational simplicity across platforms.
• Delivery Leadership & Service Transition
  • Providearchitectureleadership fromdesign through transition into managed operations.
  • DefineSLAs SLOs OLAs service catalogs and automation backlogs.
  • Guideserviceonboarding knowledge transfer (KCS) runbook creation and CMDB population.
  • Drive increased automation coverage and reduced MTTR through selfhealing and AIOps patterns.
• Governance Risk & Responsible AI
  • EmbedResponsible AIprinciples model risk management and safety controls into managed services.
  • Ensure alignment with Zero Trust SOC 2 ISO 27001 NIST GDPR HIPAA and industry regulations as applicable.
  • Define monitoring for model performance drift bias lineage and auditability.
• Practice Contribution & Thought Leadership
  • Support proposals RFPs solution design and pricing models (FTEbased consumptionbased outcomebased).
  • Mentor architects and engineers across AI automation platform and operations domains.
  • Contribute to EY assets playbooks demos and points of viewforclients and internal teams.

Skills and Attributes for Success

• A standardizedtooling blueprint and managed services frameworkadopted across multiple client engagements.

• Measurable improvements inSLA attainment MTTR reduction and automation coverage.

• Secure compliant AI servicesoperatingin production with documented controls and monitoring.

• Clear value realization tracked through KPIs FinOps metrics and client feedback.

To qualify for this role you must have

• 1214 yearsof experience in enterprise architecture platform engineering or IT operations.

• 4 yearsdesigning oroperatingmanaged services and/or SREbased operating models.

• 3 yearsworking with AI/ML or GenAI platforms (LLMs RAGMLOps).

• Strong experience integrating ITSM cloud automation observability and security tooling.

• Excellent clientfacing communication and executive storytelling skills.

Ideally youll also have

• AIenabled managed services in regulated industries.

• AutomationCoE platform engineering or cloud transformation leadership.

• Commercial experience with managed services contracts SLAs and valuebased pricing.

What we look for

We seek individuals who are proactive adaptable and eager to learn. Top performers in this role demonstrate a commitment to excellence and possess strong analytical skills enabling them to navigate complex challenges effectively.