AIML Solution Architect Agentic Automation (Managed Services) Consulting

EY Consulting is hiring an AI/ML Solution Architect to design build and industrialize agentic automation solutions for Managed Services across HR Finance Procurement Supply Chain Risk Tax and other enterprise functions. The role combines hands-on engineering with solution architecture bringing together Agentic AI GenAI workflow orchestration enterprise integration cloud-native platforms and managed-service operating models to improve productivity quality cycle time compliance and user experience.

The role is a practical technologist who can whiteboard an architecture with executives prototype an agentic workflow with engineers and guide teams through secure reliable and cost-efficient production delivery on Microsoft Azure AWS or Google Cloud Platform. The role requires strong experience with LLMs RAG agents integration patterns automation platforms MLOps/LLMOps and enterprise-grade governance.

• Design end-to-end agentic automation architectures for managed-service processes such as hire-to-retire record-to-report procure-to-pay source-to-contract order-to-cash service desk knowledge operations and compliance operations.
• Translate business outcomes into solution blueprints capability maps technical roadmaps non-functional requirements success measures and implementation backlogs.
• Define reusable reference architectures for AI agents RAG workflow orchestration human-in-the-loop review exception handling audit trails and enterprise knowledge management.
• Balance build buy and partner options across hyperscalers AI platforms automation tools enterprise SaaS and EY assets.

• Build working PoCs MVPs accelerators and production components using Python TypeScript APIs microservices event-driven patterns and cloud-native services.
• Implement RAG pipelines tool-calling agents orchestration graphs evaluation harnesses prompt and policy controls and observability dashboards.
• Develop integrations with enterprise systems such as SAP Oracle Workday ServiceNow Coupa Ariba Microsoft 365 Dynamics Salesforce and document management platforms.
• Guide engineering teams on coding standards CI/CD test automation infrastructure as code release management and operational runbooks.

• Architect secure scalable solutions on one or more hyperscaler stacks: Microsoft Azure AWS or Google Cloud Platform.
• Use native AI data integration identity security and observability capabilities including Azure AI Foundry/Azure OpenAI AWS Bedrock/SageMaker Google Vertex AI/Gemini cloud data platforms serverless services container platforms and managed Kubernetes.
• Design hybrid and regulated deployment patterns covering private networking identity federation secrets management encryption data residency model risk and compliant logging.
• Define cost-control mechanisms including model routing caching batching token governance scaling policies FinOps dashboards and usage analytics.

• Design agentic patterns such as planning routing delegation tool use memory reflection approval workflows and multi-agent collaboration for enterprise operations.
• Apply process-mining workflow and task-automation concepts to redesign managed-service processes before automating them.
• Create human-in-the-loop controls for sensitive steps such as payment approvals employee actions vendor changes reconciliations policy exceptions and regulatory submissions.
• Define measurable operating outcomes including automation rate exception rate first-time-right quality handling time SLA compliance leakage reduction and cost-to-serve improvement.

• Establish LLMOps and MLOps practices for model/prompt versioning evaluation guardrails monitoring rollback incident response and quality assurance.
• Embed AI governance controls for responsible AI data privacy access control auditability explainability model risk and regulatory compliance.
• Implement production observability across logs traces metrics user feedback groundedness hallucination risk tool execution cost per request and service-level performance.
• Lead design reviews threat modeling architecture assurance performance tuning and post-implementation optimization.

• Partner with client executives managed-service leaders function owners CIO/CTO teams and ecosystem partners to shape AI-led transformation opportunities.
• Lead discovery workshops value framing solution estimation PoVs/PoCs business cases acceptance criteria and transition plans from prototype to managed operations.
• Coach cross-functional teams across EY client and partner organizations including architects engineers data scientists process SMEs security teams and operations leads.
• Create reusable assets architecture playbooks demo journeys and delivery patterns for ASEAN priority industries and service lines.

• 10 years of experience across AI/ML solution architecture platform engineering data engineering enterprise automation or cloud-native application delivery.
• Hands-on experience delivering production AI/ML GenAI RAG conversational assistant or agentic automation solutions at enterprise scale.
• Strong proficiency in at least one major cloud stack: Microsoft Azure AWS or Google Cloud Platform including AI services data services identity/security networking and deployment patterns.
• Practical software engineering capability in Python and one or more of TypeScript Java C# or Go; strong understanding of APIs microservices integration design and testing strategies.
• Experience with LLMOps/MLOps practices such as evaluation prompt/version management model registry monitoring CI/CD guardrails and release governance.
• Knowledge of enterprise workflow and automation patterns across HR Finance Procurement Supply Chain or shared-services operations.
• Strong understanding of security privacy responsible AI data residency access control audit logging and model risk considerations.
• Client-facing consulting experience including structured problem solving executive communication workshop facilitation solution shaping and delivery leadership.

• Experience with managed-services or shared-services operating models including process transition service catalogues SLAs runbooks knowledge management and continuous improvement.
• Hands-on experience with agent frameworks and orchestration tools such as LangGraph Semantic Kernel AutoGen CrewAI OpenAI Assistants or equivalent frameworks.
• Experience with automation and workflow platforms such as Microsoft Power Platform UiPath Automation Anywhere ServiceNow Camunda Temporal Airflow or cloud-native workflow services.
• Experience integrating with ERP HCM procurement and service-management platforms such as SAP Oracle Workday Coupa Ariba ServiceNow Dynamics and Microsoft 365.
• Familiarity with vector databases and search technologies such as Azure AI Search pgvector Pinecone Milvus Redis OpenSearch Elasticsearch or BigQuery/Vertex AI search patterns.
• Relevant cloud or architecture certifications such as Azure Solutions Architect Azure AI Engineer AWS Solutions Architect AWS Machine Learning Google Professional Cloud Architect or Google Professional Machine Learning Engineer.
• Experience in regulated industries such as financial services public sector health energy or cross-border environments with data-sovereignty requirements.

• LLM application design RAG embeddings chunking hybrid search knowledge graphs tool calling function calling planning routing memory and multi-agent orchestration.
• Evaluation and safety: groundedness relevancy hallucination risk regression testing red teaming policy enforcement PII controls content moderation and prompt hardening.

• Microsoft: Azure OpenAI Azure AI Foundry Azure AI Search Azure Machine Learning AKS Functions Logic Apps Event Grid Key Vault Entra ID Purview Monitor Fabric or Synapse.
• AWS: Amazon Bedrock SageMaker Lambda Step Functions EKS ECS Glue OpenSearch DynamoDB S3 IAM KMS CloudWatch EventBridge and data lake patterns.
• Google Cloud: Vertex AI Gemini GKE Cloud Run Cloud Functions BigQuery Dataflow Pub/Sub Apigee Cloud IAM Secret Manager Cloud Logging and Cloud Monitoring.

• Python TypeScript REST/GraphQL APIs event-driven architecture containers Kubernetes Terraform/Bicep/CloudFormation GitHub Actions/Azure DevOps/GitLab CI and automated testing.
• Enterprise integration patterns for ERP HCM procurement ITSM CRM document repositories email/chat channels OCR/document intelligence and workflow engines.
• Observability and operations: OpenTelemetry Prometheus/Grafana cloud-native monitoring Langfuse/Arize/WhyLabs or equivalents incident management SLAs/SLOs and runbooks.

• Strong executive presence with the ability to simplify complex AI automation and architecture topics for business and technology leaders.
• Hands-on leadership style: comfortable moving from strategy and architecture into code prototyping troubleshooting and delivery problem solving.
• Outcome orientation with a strong focus on measurable value adoption operational resilience and continuous improvement.
• Ability to lead cross-border cross-functional teams and manage ambiguity across business technology security risk and operations stakeholders.

Singapore-based with ASEAN travel as needed for client delivery pursuits workshops and regional leadership engagements. Relocation support may be available for the right candidate.