Within the Forward Deployment Engineering (FDE) Unit, the Advisory AI Architect is a hands-on technical leader who designs and builds AI and GenAI solutions with customers. You will own key parts of the AI software stack, drive rapid proof-of-value sprints, and help move AI workloads toward stable production on Dell infrastructure, balancing speed, reliability, security, and responsible AI practices. You focus on fit-for-purpose architectures and enablement so customers can operate and extend their AI solutions after FDE Units disengage.

Join us to do the best work of your career and make a profound social impact as an Advisory AI Architect on our Forward Deployment Engineering (FDE)Team in Sydney.

What You'll Achieve

• Design scalable AI architectures for customer use cases in line with enterprise and security standards
• Lead implementation of AI software components such as model serving, orchestration, retrieval, and integrations
• Run time-bound proofs of value to demonstrate business outcomes quickly and clearly
• Help migrate AI workloads between cloud, on-premises, and hybrid environments on Dell infrastructure
• Enable customer engineers and platform teams to support and extend solutions after handover

Responsibilities

• Design, configure, and implement AI solution stacks, including model serving, orchestration, retrieval pipelines, vector stores, and related components
• Select practical tools and patterns to avoid tooling sprawl and deliver working prototypes and PoVs tied to clear success measures
• Lead PoV sprints (typically a few weeks): refine scope, build and iterate on solutions, and present outcomes and recommendations to stakeholders
• Plan and execute cloud-to-on-prem and hybrid migration patterns for AI workloads onto Dell infrastructure, optimizing performance, reliability, and security
• Take shared responsibility for production readiness and early production stability, including monitoring, performance optimization, and issue triage
• Work closely with AI Data Specialists to define and consume AI-ready data pipelines that support performance and reliability
• Collaborate with AI Strategists and Enterprise Architects to align technical scope with business outcomes and target-state architectures
• Provide documentation, runbooks, and knowledge transfer to customer teams, and contribute to Dell AI Factory reference architectures and playbooks
• Mentor other technical team members on AI architecture patterns, Dell AI infrastructure capabilities, and responsible AI practices

Take the first step towards your dream career

Every Dell Technologies team member brings something unique to the table. Here's what we are looking for with this role:

Qualifications

Essential Requirements

• Typically, 6+ years* in enterprise architecture, AI/ML platforms, or systems engineering, delivering production workloads in large enterprises
• Hands-on experience designing and implementing AI solution components such as model serving, orchestration, retrieval pipelines, vector stores, and integrations
• Strong foundation in modern software engineering practices (e.g., CI/CD, automated testing, observability, DevOps/SRE, infrastructure-as-code)
• Experience delivering and operating production AI or other large-scale distributed systems* in enterprise environments
• Demonstrated ownership of production systems, including stabilization and performance tuning in high-visibility contexts
• Ability to explain complex technical trade-offs and architectures in clear language for both technical and non-technical stakeholders
• Ability to travel to customer sites and Dell locations as needed*, in line with business requirements and applicable laws and Dell policies

Desirable Requirements

• Bachelor's degree in computer science, Engineering, Data Science, or a related field.
• Experience deploying AI solutions across cloud, on-premises, and hybrid environments.
• Familiarity with AI security, privacy, and governance and modern cloud / data / ML tooling (e.g., major public clouds, Kubernetes).
• Hands-on experience with GenAI or RAG-style solutions and leading small technical teams in customer-facing projects.