Consulting - Managed Services - AI, IT and Automation 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 <