AI/ML Solution Architect - Agentic Automation (Managed Services) - Consulting
Ernst and Young20 days ago
Singapore, SingaporeStaff+
Responsibilities
- Design reusable end-to-end architectures for agentic automation and managed-service processes.
- Translate business outcomes into solution blueprints, roadmaps, non-functional requirements, success measures, and implementation backlogs.
- Build 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, policy controls, and observability dashboards.
- Architect secure and scalable solutions on Microsoft Azure, AWS, or Google Cloud, including networking, identity, security, deployment, data residency, and cost controls.
- Develop integrations with ERP, HCM, procurement, CRM, service-management, document, and collaboration platforms.
- Establish LLMOps/MLOps practices for versioning, evaluation, guardrails, monitoring, rollback, incident response, and release governance.
- Lead threat modeling, architecture reviews, performance tuning, governance, risk management, and post-implementation optimization.
- Partner with client executives and stakeholders to lead discovery workshops, value framing, solution estimation, PoCs, business cases, and transition plans.
- Coach cross-functional EY, client, and partner teams and create reusable architecture playbooks and delivery assets.
Requirements
- 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.
- Practical software engineering capability in Python and one or more of TypeScript, Java, C#, or Go, with strong knowledge of APIs, microservices, integration design, and testing strategies.
- Experience with LLMOps/MLOps practices including evaluation, prompt and model versioning, model registries, monitoring, CI/CD, guardrails, and release governance.
- Knowledge of enterprise workflow and automation patterns across HR, Finance, Procurement, Supply Chain, or shared-services operations.
- Understanding of security, privacy, responsible AI, data residency, access control, audit logging, and model risk.
- Client-facing consulting experience involving structured problem solving, executive communication, workshop facilitation, solution shaping, and delivery leadership.
- Preferred experience with managed-services or shared-services operating models, agent frameworks, workflow platforms, enterprise systems, vector databases, search technologies, cloud or architecture certifications, and regulated industries.
- Ability to lead cross-border, cross-functional teams and explain complex AI, automation, and architecture topics to business and technology leaders.
Benefits
- Singapore-based role with ASEAN travel as needed for client delivery, pursuits, workshops, and regional leadership engagements.
- Relocation support may be available for the right candidate.
Tech Stack
Amazon DynamoDBApache AirflowAWSAzureC#ElasticsearchGitHub ActionsGitLab CI/CDGoGoogle BigQueryGoogle Cloud PlatformGrafanaGraphQLJavaKubernetesPrometheusPythonRedisTerraformTypeScript
Categories
Solutions Engineering
About Ernst and Young
Ernst & Young (EY) provides audit/assurance, tax, consulting, strategy and transactions services to enterprises, financial institutions, and public‑sector clients. Structured as a global network of partner‑owned member firms, it sells professional services on a fee basis, including a dedicated Financial Services Organization for banking, insurance, and capital markets. Headquartered in London, EY was formed in 1989 from the merger of Ernst & Whinney and Arthur Young, and operates in 150+ countries.