Consulting - Managed Services - AI, IT and Automation Senior Manager

Managed Services AI, IT & Automation Architect, Senior Manager

EY is seeking a client‑facing Managed Services AI, IT & Automation Architect (Senior Manager) to design, operationalize, and scale AI‑enabled managed services for our clients. This role is accountable for orchestrating the end‑to‑end tooling strategy across AI, automation, cloud, ITSM, and observability, and for creating a compelling, reusable framework that enables clients to move from experimentation to enterprise‑grade, production‑ready managed services. 

The Senior Manager will balance hands‑on 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 technologies, DevSecOps, ITSM, and observability into a coherent, supportable managed services ecosystem. 
• Create a compelling framework: Define a practical, repeatable AI‑led Managed Services Framework that 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 business objectives into managed service architectures, platform roadmaps, and operating models. 
  • Develop business cases (TCO/ROI) and outcome‑based value narratives tied to cost reduction, resiliency, speed, and risk mitigation. 
  • Present executive‑level recommendations explaining tooling choices, trade‑offs, and long‑term sustainability. 
• Reference Architecture & Framework Development 
  • Design, document, and evolve EY’s AI‑Led 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, event‑driven patterns 
    • AI & Automation: GenAI, LLM/RAG patterns, MLOps, RPA/ITPA orchestration 
    • Security & Risk: identity, data protection, Responsible AI guardrails 
    • SRE & Observability: SLOs/SLIs, error budgets, runbooks, auto‑remediation 
    • FinOps: unit economics, cost optimization, capacity management 
  • Produce reference architectures, decision matrices, control catalogs, and reusable accelerators. 
• Platform & Tooling Orchestration 
  • Architect and integrate end‑to‑end toolchains spanning:  
    • Cloud & DevSecOps: Azure (preferred), AWS, GCP; Kubernetes; Terraform; GitHub/Azure DevOps; GitOps 
    • Data & AI: Azure OpenAI, Databricks, Snowflake, vector databases, MLOps pipelines, prompt/version management 
    • Automation: UiPath, Power Automate, Azure Automation, event‑driven 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 
  • Provide architecture leadership from design through transition into managed operations. 
  • Define SLAs, SLOs, OLAs, service catalogs, and automation backlogs. 
  • Guide service onboarding, knowledge transfer (KCS), runbook creation, and CMDB population. 
  • Drive increased automation coverage and reduced MTTR through self‑healing and AIOps patterns. 
• Governance, Risk & Responsible AI 
  • Embed Responsible AI principles, 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 (FTE‑based, consumption‑based, outcome‑based). 
  • Mentor architects and engineers across AI, automation, platform, and operations domains. 
  • Contribute to EY assets, playbooks, demos, and points of view for clients and internal teams. 

Skills and Attributes for Success

• A standardized tooling blueprint and managed services framework adopted across multiple client engagements. 

• Measurable improvements in SLA attainment, MTTR reduction, and automation coverage. 

• Secure, compliant AI services operating in 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

• 12–14+ years of experience in enterprise architecture, platform engineering, or IT operations. 

• 4+ years designing or operating managed services and/or SRE‑based operating models. 

• 3+ years working with AI/ML or GenAI platforms (LLMs, RAG, MLOps). 

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

• Excellent client‑facing communication and executive storytelling skills. 

Ideally, you’ll also have

• AI‑enabled managed services in regulated industries. 

• Automation CoE, platform engineering, or cloud transformation leadership. 

• Commercial experience with managed services contracts, SLAs, and value‑based 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.