UX Engineer - AI and Applications

Firmus Technologies

Firmus Technologies is a global leader pioneering the development and operation of efficient AI infrastructure across Asia Pacific.

Founded in Australia in 2019, our mission is to create the most efficient AI infrastructure by combining cutting-edge technology with a steadfast commitment to sustainability. 

At Firmus, we are unique in our approach. We design, build, and operate a new class of digital infrastructure – the AI Factory. Through our model-to-grid technology approach, we have pushed the boundaries of multi-generational liquid cooling systems, energy management, AI software orchestration, and construction. For our customers, this approach allows us to make every watt count and deliver low-cost AI tokens globally.

Firmus AI Cloud

Our large-scale GPU cloud platform, Firmus AI Cloud, is purpose-built to deliver energy-efficient AI compute at scale to customers.

It empowers developers, enterprises, educational institutions, and government users to train and deploy AI models with unmatched efficiency and cost savings. With an ever-growing suite of services and applications, we are committed to delivering a cloud experience that is market-leading, proprietary, and built to scale.

Why Firmus?

As an NVIDIA Cloud and Engineering partner in Asia Pacific, you will gain skills, experience, and exposure across the AI industry and be part of shaping what this industry looks like for decades to come.

We are founder-led, not a big corporate. Decisions happen fast, our leaders are accessible, and there's minimum bureaucracy between you and the work. Ownership comes early. Whatever your role, you will have a direct line to outcomes, helping shape how the business grows as we scale nationally across a long-term, large-scale roadmap. 

Work alongside founders and experts in AI infrastructure, energy systems and next-generation compute.

What we build here has impact beyond the business. Our AI Factories are designed to operate as assets to the energy grid to actively strengthen the communities and regions they operate in rather than drawing from them.

Considering applying? You don't need a perfect background to join our team. If you're driven and curious, there's a path for you. We back our people to grow into new domains and take on challenges beyond their previous experience.

Role Summary

The UX Engineer will define and deliver intuitive, coherent, and technically credible user experiences across the AI & Applications team’s internal and external product portfolio. The role will shape how users discover, provision, operate, optimize, and troubleshoot AI infrastructure and AI-powered services through products such as the AI Cloud Portal, Global Operations Console, Bare Metal as a Service, Kubernetes as a Service, and future X-as-a-Service offerings.

This role sits at the intersection of user experience design, front-end engineering, product thinking, and AI-platform understanding. The UX Engineer will translate complex infrastructure and AI capabilities—including GPU capacity, bare-metal provisioning, Kubernetes clusters, workload scheduling, benchmark results, model recipes, inference services, Model-to-Grid optimization, and agentic operations—into clear workflows, understandable interfaces, and actionable experiences for customers, developers, AI researchers, support teams, operators, and internal delivery teams.

A central focus will be making sophisticated AI-factory capabilities usable. The UX Engineer will help users understand and act on model-to-grid recommendations, scheduler decisions, workload placement, cluster health, benchmark outcomes, capacity availability, performance bottlenecks, inference cost, energy or power signals, and agent-generated operational insights. The role will ensure that advanced automation remains transparent, controllable, auditable, and trustworthy—particularly where agentic systems recommend or execute actions.

The UX Engineer will report to the Head of AI & Applications, working closely with other AI engineers, DevOps and scheduler engineers, inference and optimization engineers, platform,infrastructure, security, global operations, and customer-facing teams. The role will create a scalable design system and product experience that supports both immediate platform needs and future AI-factory and XaaS product expansion.

Key Responsibilities

• Own end-to-end UX design and front-end experience quality for the AI Cloud Portal, Global Operations Console, Bare Metal as a Service, Kubernetes as a Service, and future XaaS products.
• Conduct user discovery and workflow analysis with key personas, including AI researchers, ML engineers, application developers, cloud administrators, tenant administrators, infrastructure operators, support engineers, data-centre teams, and external customers.
• Translate product requirements, user needs, operational workflows, technical constraints, and system telemetry into user journeys, information architectures, wireframes, prototypes, interaction patterns, and production-ready interfaces.
• Design self-service experiences for discovering, requesting, provisioning, configuring, accessing, monitoring, scaling, updating, and decommissioning bare-metal GPU capacity and Kubernetes environments.
• Design clear workflows for GPU and AI workload management, including job submission, job templates, model and workload recipes, queue selection, quota visibility, priority requests, capacity reservations, workload status, failures, retries, and support escalation.
• Create usable interface patterns that explain proprietary scheduler decisions, including why a job is queued, admitted, deferred, placed on a particular topology, pre-empted, rescheduled, or unable to run.
• Design Model-to-Grid experiences that help users and operators understand the relationship between model or workload requirements, benchmark results, GPU resources, network topology, storage, capacity, power, thermal conditions, and scheduling outcomes.
• Create user-facing workflows for selecting and applying validated model, training, fine-tuning, and inference recipes based on workload goals such as latency, throughput, accuracy, cost, energy efficiency, GPU availability, or time-to-results.
• Design intuitive benchmarking experiences, including benchmark configuration, execution tracking, result exploration, comparison of baselines and variants, reproducibility metadata, bottleneck identification, and actionable optimizationrecommendations.
• Shape the Global Operations Console experience for monitoring and managing fleet-level AI-factory operations, including cluster health, capacity, workload demand, infrastructure events, service status, scheduler health, resource utilization, maintenance activities, and operational incidents.
• Make complex infrastructure status and telemetry actionable through dashboards, drill-down views, alerts, guided troubleshooting, root-cause context, recommended actions, and role-appropriate escalation paths.
• Design agentic application experiences that clearly distinguish between agent observations, recommendations, planned actions, approved actions, completed actions, failures, and human intervention points.
• Create safe and trustworthy human-in-the-loop workflows for agentic operations, including approval queues, permission scopes, action previews, confidence or evidence views, audit trails, rollback options, and incident escalation.
• Design user experiences for AI platform identity, access, tenancy, quotas, approvals, notifications, billing or consumption visibility, support, and administrative controls in partnership with Security and platform teams.
• Develop and maintain a scalable design system, component library, interaction standards, accessibility guidelines, content patterns, and visual language suitable for cloud, AI-platform, and operations-console products.
• Implement high-quality front-end experiences or work closely with front-end engineers to ensure designs are technically feasible, performant, responsive, accessible, and consistently implemented.
• Partner with the Product Manager / TPM / Release Manager to define user-facing product requirements, UX acceptance criteria, phased release plans, usability validation, release notes, product documentation, and adoption measures.
• Work with AI, DevOps, Platform, SDI, Security, and operations teams to ensure interfaces accurately represent system state, operational constraints, permissions, data freshness, risk level, and action consequences.
• Define and analyze UX metrics, customer feedback, product analytics, workflow completion, feature adoption, support trends, task duration, error rates, and usability findings; use them to prioritize iterative improvements.
• Champion a product-led, user-centered approach across technical teams by making user workflows, usability risks, and customer outcomes visible early in product definition and delivery.

Skills & Experience

• 5+ years of experience in UX engineering, product design, interaction design, front-end engineering, or a comparable role delivering enterprise, developer, cloud, or operational software products.
• A portfolio demonstrating end-to-end design and delivery of complex web applications, platforms, control planes, developer tools, cloud consoles, data-intensive products, or operational dashboards.
• Strong ability to convert complex technical systems and workflows into intuitive user journeys, information architecture, interaction models, and production-quality interfaces.
• Practical experience designing for multiple user personas, permission levels, account or tenant boundaries, high-stakes operations, self-service workflows, and complex configuration tasks.
• Proficiency in modern product-design tools such as Figma or comparable tools for wireframing, prototyping, design systems, user flows, and developer handoff.
• Strong front-end engineering capability in modern web technologies, such as TypeScript, JavaScript, React, Next.js, Vue, Angular, or equivalent frameworks.
• Experience building or contributing to component libraries, design systems, responsive web applications, data visualization patterns, and accessible user interfaces.
• Understanding of user research, usability testing, user interviews, workflow mapping, prototype validation, product analytics, A/B testing where appropriate, and iterative design methods.
• Familiarity with cloud infrastructure, Kubernetes, bare-metal provisioning, distributed systems, observability, job scheduling, developer platforms, or infrastructure operations.
• Technical curiosity and the ability to understand AI/ML platform concepts, including GPU resources, distributed workloads, training, inference, model serving, benchmarking, workload recipes, queues, quotas, and performance metrics.
• Ability to interpret metrics and telemetry relevant to AI-platform interfaces, including GPU utilization, queue time, job state, workload status, cluster health, latency, throughput, capacity, error rates, cost, and energy-related indicators.
• Familiarity with AI application patterns, including RAG, agentic workflows, model recommendations, human approval flows, AI-generated insights, confidence and provenance indicators, and conversational or copiloted interfaces.
• Experience designing security-conscious user experiences involving authentication, RBAC, tenant boundaries, approval workflows, secrets or credentials, auditability, privacy, and controlled actions.
• Strong written communication skills, including ability to produce concise UX rationale, interaction specifications, content guidance, workflow documentation, and releaseready design artefacts.

Location & Reporting

• Location: Singapore
  
• Reports to: Head of AI & Applications

Employment Basis

Permanent full-time

Diversity

At Firmus, we are committed to building a diverse and inclusive workplace. We encourage applications from candidates of all backgrounds who are passionate about creating a more sustainable future through innovative engineering solutions.

Join us in our mission to revolutionise the AI industry through sustainable practices and cutting-edge engineering. Apply now to be part of shaping the future of sustainable AI infrastructure.