AI Architect (Forward Deployment Engineering)

Dell Technologies Inc.; Sydney; On-site; AUD 260,000 - 360,000; Full time

Job summary

Dell Technologies in Sydney is seeking an AI Architect in the Forward Deployment Engineering team. You will lead hands-on design and build of AI solution stacks, drive PoVs, and move workloads toward production on Dell infrastructure.

The role emphasizes fit-for-purpose architectures, collaboration with AI data specialists and enterprise architects, and mentoring others on responsible AI.

Travel to Australia and New Zealand is required; a Bachelor's in CS/Engineering/Data Science is preferred.

Qualifications

• Hands-on experience designing and implementing AI solution components (model serving, orchestration, retrieval pipelines, vector stores)
• 6+ years in enterprise architecture, AI/ML platforms, or systems engineering
• Strong software engineering practices (CI/CD, automated testing, observability, DevOps/SRE, infrastructure-as-code)
• Experience delivering production AI or other large-scale distributed systems in enterprise environments
• Experience deploying AI solutions across cloud, on-premises, and hybrid environments
• Demonstrated ownership of production systems, including stabilization and performance tuning

Responsibilities

• Design, configure, and implement AI solution stacks, including model serving, orchestration, retrieval pipelines, vector stores, and related components
• 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

Skills

AI solution design

CI/CD

Automated testing

Observability

DevOps/SRE

Infrastructure as Code

GenAI/RAG patterns

Cloud/Hybrid architecture

Production systems ownership

Stakeholder communication

Education

Bachelor's degree in computer science, engineering, data science, or related field

Tools

Kubernetes

Job description

Within the Forward Deployment Engineering (FDE) Unit, the 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 AI Architect on our Forward Deployment Engineering (FDE) Team in Sydney.

What You'll Achieve

• 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:
• Hands-on experience designing and implementing AI solution components such as model serving, orchestration, retrieval pipelines, vector stores, and integrations
• 6+ years in enterprise architecture, AI/ML platforms, or systems engineering, delivering production workloads in large enterprises
• 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
• Experience deploying AI solutions across cloud, on-premises, and hybrid 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 in Australia and New Zealand, in line with business requirements and applicable laws and Dell policies
• Bachelor's degree in computer science, Engineering, Data Science, or a related field
• 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