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Salary
≈ $114k – $227k per year (Estimated)
Location
In office (London)
Seniority
Staff
Employment
Full-Time

Confirmed on the employer's own hiring board on Sep 29, 2026. First seen by Alion on Sep 28, 2026. WhyHireWrong scores A on the Alion truth index.

Overview
Company
Impact
Profile match
Headquartered in Warsaw, Poland, WhyHireWrong? is a boutique tech talent acquisition agency dedicated to transparent hiring processes for technology, product, and engineering roles. The company offers specialized recruitment and career placement services combining role-specific candidate video assessments, resume optimization, and direct employer introductions. By enforcing strict zero-ghosting policies and pre-verifying candidate intent, it helps fast-growing technology companies reduce hiring risks and streamline their recruitment pipelines.

About the role

This role takes technical ownership of the core product: the end-to-end game generation pipeline. The person in this role will scale the system to drive up the playability pass rate while driving down the cost per generation at volume. Work spans the full AI generation loop: generation, validation, repair, and evaluation.

Responsibilities

- Own the end-to-end game generation pipeline from prompt to running browser game

- Build and maintain automated validation and repair loops for AI-generated code and assets

- Reduce cost per generation through tiered model routing, caching, distillation, and other LLM economics optimizations

- Integrate AI generation pipelines directly with web game runtimes (Three.js, Phaser, Babylon, WebGL)

- Work with procedural content generation systems for game mechanics and assets

- Lead a small team of 2-3 engineers on the AI generation stack

- Ship production code that compiles and runs complex AI-generated outputs in browser game environments

Requirements

- Shipped text-to-game, AI game-creation tech, or a prompt-to-running-app agent at scale

- Experience owning a full AI generation loop (generation, validation, repair, evaluation)

- Proven track record of cutting cost per generation in an LLM pipeline while maintaining output quality (via tiered model routing, caching, distillation, or similar)

- Hands-on engineering experience with web game runtimes (Three.js, Phaser, Babylon, WebGL) or procedural content generation

- Understanding of basic ML mathematics and LLM systems (not just prompt engineering or research)

- Experience beyond basic LLM wrappers; must have shipped production code that compiles and runs complex AI-generated outputs

- Not from a consultant, agency, or B2B employment setup; must be full-time

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