Frontend Engineer — AI Infrastructure Platform

We are looking for a Senior Frontend Engineer to build the frontend of our AI infrastructure platform. Clients use our platform to access and operate two technical products, and the role is to make those products understandable, reliable, and powerful through high-quality frontend engineering.

This is not a standard SaaS frontend role and not the usual one-page-application frontend job. You will work on a technical B2B platform where the frontend must represent complex infrastructure workflows, system states, data-heavy interactions, and product logic in a way that expert users can trust and use efficiently.

• Own frontend implementation for key areas of the AI infrastructure platform, covering both Scheduler and Simulator.

• Build the Scheduler experience for live operational workflows: real-time infrastructure state, workload placement, utilization, throughput, bottlenecks, alerts, and remediation paths.

• Build the Simulator experience for planning workflows: hypothetical buildouts, scenario comparison, capacity planning, cost-performance modeling, and ROI-oriented decision support.

• Develop shared frontend components and product patterns that make both products feel coherent while supporting different mental models for live operations and exploratory simulation.

• Translate complex concepts such as GPU topology, heterogeneous accelerators, scheduling decisions, resource allocation, utilization tradeoffs, latency, power, and cost into robust frontend workflows and visualizations.

• Implement data-dense interfaces that are scannable, responsive, trustworthy, and useful for technical users without becoming a spreadsheet, generic admin UI, or Grafana-style wall of charts.

• Partner closely with product, backend, infrastructure experts, and leadership to understand technical constraints and turn them into customer-facing frontend solutions.

• Contribute to frontend architecture, component quality, state management, performance, accessibility, testing, and maintainability across the platform.

• Work with APIs, data models, real-time or near-real-time states, error states, loading states, permissions, and edge cases that are critical in infrastructure products.

• Challenge generic frontend approaches and propose modern, differentiated solutions that build trust in high-stakes operational and capital-expenditure decisions.

• 5+ years of frontend engineering or product engineering experience, with clear senior-level ownership of complex product work.

• Strong experience with modern frontend technologies such as React, TypeScript/JavaScript, component-driven development, frontend testing, and state management.

• Evidence of shipped, data-dense, technically complex B2B products where you improved clarity, reliability, performance, and usability through frontend implementation.

• Strong product thinking and the ability to understand technical systems deeply enough to build for real expert workflows without oversimplifying the product or losing important signal.

• Experience building complex B2B products such as developer tools, cloud platforms, observability/monitoring, data platforms, DevOps, AI/ML tooling, simulation tools, fintech/trading dashboards, or other technical enterprise products.

• Ability to work with product and engineering stakeholders to turn ambiguous technical requirements into pragmatic frontend architecture and implementation plans.

• Experience with dashboards, monitoring views, configuration flows, comparison views, capacity planning, metrics, alerts, logs, tables, or other dense quantitative interfaces.

• High standards for frontend quality: maintainable code, thoughtful abstractions, performance awareness, accessibility, reliable testing, and clean integration with backend APIs.

• Comfort working directly with backend engineers, infrastructure experts, product managers, and technical stakeholders in ambiguous, fast-moving environments.

• Senior-level independence: able to structure messy problems, challenge assumptions, identify frontend risks, make trade-offs, and deliver without detailed supervision.

• Experience with AI infrastructure, GPU platforms, heterogeneous compute, cloud infrastructure, Kubernetes, schedulers, simulators, MLOps, data platforms, or distributed systems.

• Understanding of GPU-level infrastructure concepts such as topology, accelerators, workloads, tenants, quotas, capacity, utilization, latency, throughput, memory, or power constraints.

• Experience building planning, simulation, scenario-modeling, CAD-like, graph, topology, or comparison tools.

• Experience with observability, monitoring, incident response, or other real-time operational interfaces.

• Experience with custom data visualization, complex tables, network/topology views, Web Workers, or other advanced frontend implementation patterns.

• Experience building multi-product platform experiences where several products share components, architecture, and platform conventions but require distinct workflows.

• Experience working with technical users, infrastructure teams, or executive stakeholders making ROI decisions.

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