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

Most backend roles ask you to ship endpoints and migrations. This one asks you to ship those and extend the platform that lets the rest of the engineering team - and the AI agents working alongside them - ship them too. That platform already exists.

Shared conventions, the skills library, safe contribution zones, spec-to-endpoint workflows, AI-agent infrastructure powering Saige and Explore - all live, all in production, all being used today. You'll own its next chapter: deepening it, scaling it, and raising the ceiling on what each engineer can do without re-deriving the same patterns. " - keep reading.

What will you own You own the backend - not just the code you write, but the system that lets everyone around you contribute to it. That means shipping production Rails services, designing APIs other teams build against, and owning the data layer end to end. And it means extending the workflows, conventions, and guardrails that let QEs generate test scaffolds independently, PMs and analysts ship config and feature-flag changes safely, and AI agents operate inside the codebase reliably.

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: Shared AI conventions that keep tooling output consistent across the codebase - for backend code generation, schema changes, and migrations - whoever or whatever is driving A backend skills library that encodes Rails patterns, service contracts, domain models, and query patterns into workflows anyone on the team can invoke Safe zones and guardrails that let PMs and analysts ship config changes, feature flags, and scoped data changes without creating engineering cleanup Spec-to-endpoint and ticket-to-migration workflows that compress the path from intent to working backend code AI-agent backend infrastructure - runtimes, tool-calling layers, retrieval pipelines, evals - that powers Saige, Explore, and what comes next, and scales with each new feature A feedback loop with engineers, QEs, and PMs building against the platform every day - you hear where things break and you fix them What success looks like 30 days.

You've mapped the existing platform, the conventions, the skills library, and the AI workflows the team is already using. You know where they're sharpest, where they're starting to bend under load, and where the next wave of investment should go. 90 days.

You've shipped meaningful additions to the skills library, tightened conventions where they were drifting, and closed gaps the team has been working around. Other engineers are reaching for your work instead of writing from scratch. 6 months.

The backend platform is materially more capable than when you joined. Saige and Explore's AI surfaces hold up under heavier production load because of infrastructure decisions you made. PMs and analysts are shipping more inside safe zones, with less cleanup.

The engineers and agents building against the platform move faster - and they know why.

Qualifications

Bachelor's degree in Computer Science, Engineering, or a related field - or equivalent practical experience Experience 5+ years of backend engineering experience on production systems Strong production Rails experience - services you've owned and shippe

Senior Backend Platform Engineer, AI Enablement (Rails)