Frontend Platform Engineer, AI Enablement (Angular)

About this role

About Manifest Global

Manifest Global is building the infrastructure for global human capital mobility - connecting students, schools, universities, and employers across 50+ countries. Our portfolio spans Cialfo (AI-powered college counseling, 2,000+ schools), BridgeU (university guidance for international schools globally), Kaaiser (trusted study abroad counseling across India and Southeast Asia), and Explore (AI-powered university outreach, 1,000+ university partners). Together, we move talent across borders at scale. $80M raised. Still early.

About This Role

This is an AI-first frontend role. We don't mean you'll use Copilot on the side, we mean AI is the medium you work in, and the capability you extend to everyone around you. The Manifest engineering team already runs on AI-assisted workflows. Shared conventions, a live skills library, and cross-functional AI workflows are in production today. You'll complete that system, maintain it, and raise the ceiling on what QEs, PMs, and designers can do without engineering in the loop.
Most frontend roles ask you to ship features. This one asks you to ship features and build the system that lets everyone else ship them too, safely, independently, with AI as the connective tissue.
If you're early in your career and the most interesting question you have right now is "how do I build leverage for a team, not just output for myself?" - keep reading.

What You'll Own

You own the frontend; not just the code you write, but the system that lets everyone around you contribute to it. That means building features, and it means building the workflows, conventions, and guardrails that let QEs test independently, PMs contribute safely, and designers move from design to something real without waiting in a queue.

The measure of success here is not your personal output. It is how much the team around you can do because of what you built.

Concretely, that looks like:

• The shared AI conventions that keep tooling output consistent across the codebase, whoever is driving

• A skills library that encodes frontend patterns, API contracts, and business logic into workflows anyone on the team can invoke

• Safe zones and guardrails that let non-engineers contribute without creating engineering cleanup

• Design-to-code workflows that unblock designers without dev involvement

• A feedback loop with QEs, PMs, and designers - you hear where things break and you fix them

What Success Looks Like

• 30 days. You've mapped the frontend architecture and the current cross-functional AI workflows. You know where the codebase is strong, where debt sits, and where QEs, PMs, and designers are getting stuck or falling back on engineering. You have a point of view on what to fix first.

• 90 days. The skills library has grown. QEs are generating test scaffolds from specs without filing requests to engineering. PMs are making frontend…