About Kyra

Kyra is an enterprise influencer marketing platform working with brands like SharkNinja, Coach, H&M, Ray-Ban, and Converse. Our platform manages the full lifecycle — creator discovery, campaign management, content review, payments, analytics, and AI-powered intelligence across TikTok, Instagram, and YouTube.

THE ROLE

We’re looking for a senior backend engineer with sharp product judgement. You’ll work alongside our engineering lead on a platform that processes millions of creator data points, runs real-time analytics, and powers AI-driven workflows.

This isn’t a “wait for a fully-scoped ticket” role. You’ll take ambiguous direction, make calls, and ship features end-to-end — including deploying them yourself. We have infra already; we need someone who can operate inside it confidently, not someone who wants to rebuild it.

WHAT YOU’LL ACTUALLY DO

• Build and maintain domain modules in a DDD-style Node.js/TypeScript monorepo.

• Take vague product direction, sharpen it into a real spec, and ship a v1 — then iterate.

• Design APIs, write docs, and manage database schemas and migrations.

• Build features that span our main transactional backend and a separate analytics backend running heavy queries over creator data.

• Write services that integrate with TikTok, Instagram, and YouTube APIs.

• Work with queue workers for background job processing (media analysis, outreach, data syncing).

• Deploy your own services to our cloud infrastructure, write the migrations, watch them go out safely.

• Investigate production issues when they touch your code — trace through the observability stack to find the cause.

REQUIRED — NON-NEGOTIABLE

• 6+ years backend development with Node.js and TypeScript in production.

• Product mindset — you’ve shipped features where the brief was a paragraph, not a ticket. You ask why before how, make calls when requirements are vague, and iterate after release. You’ve sat across from non-engineers and left with a sharper problem than you walked in with.

• Strong relational database experience — schema design, query optimisation, safe migrations at scale.

• Comfortable deploying and operating your own services on a major cloud provider — containers, CI/CD pipelines, the basics of running things in production. You don’t need to be an infra specialist, but you don’t need handholding either.

• Queue-based background job processing patterns.

• REST API design and documentation.

• Git workflow maturity — branching strategies, code review, migration safety. You understand why you don’t run destructive commands on a production migration.

STRONGLY PREFERRED

• Shipped AI features to production — you know what evals are for, why prompts regress, and why “it worked in testing” isn’t enough.

• Columnar / analytics databases for heavy aggregate queries.

• In-memory caching and session stores.

• DDD or domain-driven design — explicit module boundaries, repositories, services, event-driven patterns.

• Production observability — you’ve triaged real issues, not just configured dashboards.

• OAuth, OTP, or session-based auth systems in production.

NICE TO HAVE

• Social media platform APIs (TikTok, Instagram, YouTube).

• Search infrastructure for large datasets.

• Monorepo tooling and workflows.

• Side projects, OSS contributions, or tools you’ve built for yourself that other people now use — signal that you ship for the love of shipping.

WHAT THIS PERSON LOOKS LIKE

• Holds opinions and changes them fast — you’ll ship the wrong thing sometimes and replace it a week later. That’s the job.

• Debugs across boundaries — when a metric shows the wrong number, you can trace it from the frontend component through the API layer down to the database query and figure out where it breaks.

• Writes code that doesn’t need babysitting — proper validation, error handling, and patterns other team members can follow.

• Communicates proactively — posts in Slack when deploying, writes migration plans before running them, documents API contracts for the frontend team.

• Moves fast without breaking things — we deploy to production multiple times a week. You should be comfortable with that cadence while still being careful.

TEAM

A small, high-output engineering team (~10 people) led by the current engineering lead. Async standups, weekly refinement, ship directly to production.

This is a heavy AI-usage environment — AI tooling is woven into how we build, review, and ship. Comfort using it daily is expected.

💟 Support

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