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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in designing scalable AI infrastructure solutions, translating customer requirements into technical specifications, and leading cross-functional collaboration among Product Management, Engineering, and Operations teams. Proficient in delivering technical workshops and developing best practices for AI workloads and cloud-native architectures.
Highest-signal resume keywords
AI InfrastructureKubernetesGPU PlatformsTechnical DiscoveryCloud-Native Architectures
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Solutions ArchitectureInfrastructure AutomationInfrastructure-as-CodeHigh-Performance ComputingMLOpsDistributed TrainingInference WorkloadsTechnical Proof-of-ConceptsArchitecture ReviewsDeployment Patterns
Soft Skills
Strong Communication SkillsCustomer Engagement
Tools & Technologies
Bare MetalBMaaSCloud-Native PlatformsData-Centre InfrastructureHigh-Performance Networking
Industry Keywords
Public SectorDefenceHealthcareRegulated EnvironmentsProduct Strategy
Tech Stack
Tools & technologiesCloudKubernetes
About the role
Key responsibilities & impact- Lead technical discovery with customers to understand AI workloads, infrastructure requirements, sovereignty needs, and success criteria
- Design scalable solutions across Bare Metal, BMaaS, Kubernetes platforms, and AI infrastructure services
- Own technical proof-of-concepts, pilots, benchmarks, and architecture reviews
- Act as the voice of the customer, identifying product gaps and influencing roadmap priorities
- Develop reusable reference architectures, deployment patterns, and best practices
- Translate customer demand into infrastructure, capacity, networking, and service requirements for future Era4 sites
- Define onboarding, readiness, and production transition requirements across Engineering, Operations, PMO, and Customer Success teams
- Deliver technical workshops for customers, partners, and internal teams
- Bridge customers, Product Management, Engineering, Operations, and Delivery teams to support adoption of Era4's AI infrastructure services
Requirements
What you’ll need- Proven experience in a customer-facing Solutions Architect, Solutions Engineer, Cloud Architect, or Technical Consultant role
- Strong understanding of AI infrastructure, GPU platforms, Kubernetes, and cloud-native architectures
- Ability to translate customer requirements into scalable, supportable technical solutions
- Experience leading technical discovery, architecture reviews, proofs of concept, and customer workshops
- Strong communication skills with the ability to engage both technical and executive stakeholders
- Experience working closely with Product, Engineering, Operations, and commercial teams
- Experience in one or more of: AI/ML infrastructure, GPU platforms, distributed training, inference workloads, high-performance computing (HPC) environments, Kubernetes platform engineering, MLOps, cloud-native platform operations, infrastructure automation, Infrastructure-as-Code, large-scale storage, high-performance networking, data-centre infrastructure, product strategy, roadmap development, customer onboarding, service transition, technical account management, sovereign cloud, public sector, defence, healthcare, or other regulated environments
Benefits
Comp & perks- Mission-driven start-up building critical national infrastructure
- High visibility with leadership
- Real autonomy
- Opportunity to shape how a next-generation company operates at scale
- Inclusive environment
- Equal opportunity employer