FI
AI-Native Full-stack Engineer
- Hiring from
- Probably Worldwide
- Work type
- Remote
- Posted
621,137 remote jobs, straight from company career pages
100% free · New jobs every minute
Show job descriptionHide job description
Role description
The engineer builds gamification features on an established iGaming platform: player-facing website, core API, back office. AI agents write most of the code. The engineer owns the plan, the technical decisions and the quality of each merge request.
Tech stack
- Backend: Node.js (Express, Fastify, NestJS), TypeScript, PHP (CodeIgniter 3)
- Frontend: Vue 3 (Pinia, Vite)
- Data and messaging: MySQL, MongoDB, Redis, RabbitMQ, Bull, ClickHouse, PostgreSQL
- Infrastructure: Docker, GitLab CI
- AI tooling: Claude Code (primary), Cursor, MCP
Must have skills
- 4+ years of commercial software development, including 3+ years of backend work in Node.js and TypeScript.
- 1+ year of daily agentic development with Claude Code or a similar tool on real projects: plan mode, subagents, parallel sessions in git worktrees.
- At least one spec-driven approach used on a real project (Superpowers, Spec Kit, OpenSpec, BMAD, Kiro or an in-house process).
- Ability to write and maintain agent context: AGENTS.md or CLAUDE.md, skills, rules, hooks, permissions.
- Solid Vue 3 (Composition API, Pinia). Gamification is player-facing work, so each engineer also builds the UI part of a feature.
- Hands-on MySQL, MongoDB, Redis and message queues (RabbitMQ or Bull).
- Experience with legacy code that has no tests: characterization tests, safe refactoring.
- Understanding of AI development risks: secrets and personal data in agent context, review of AI-written code.
- English at B2 (Upper-Intermediate) or higher.
- Ukranian or russian fluent speaking.
Responsibilities
- Turn product requirements from the product team into specs with acceptance criteria and keep the specs in the repository.
- Deliver each feature through spec, technical plan, task breakdown, implementation and verification. - Keep the agent context for the gamification area current: AGENTS.md, CLAUDE.md, skills, slash commands, subagents, MCP.
- Cover critical paths with tests, including characterization tests around legacy code, so agents can verify their own work.
- Describe the contracts the features depend on (queues, APIs, shared tables) in a machine-readable format.
- Work within the team's quality gates: permissions, hooks, automatic lint, AI-assisted code review in GitLab CI.
- Review AI-written code to the same standard as human-written code. Keep secrets and personal data out of agent context.
- Work across several repositories together with the in-house development team.
Nice to have
- iGaming experience, especially bonus mechanics and player engagement features such as missions, tournaments, leaderboards or loyalty levels. Fintech experience (payments, KYC, provider integrations) also counts. Candidates without domain experience still qualify.
- Product experiments: feature flags, A/B tests, segmentation, retention and conversion metrics.
- Event-driven features built on player events (queues, WebSockets) and integrations with external gamification or CRM services.
- PHP and CodeIgniter 3.
- NestJS, Fastify, ClickHouse, PostgreSQL.
- GitLab CI pipelines and AI-assisted code review in CI.
- Building MCP servers or Claude Code plugins.
- Public examples of AI practice: skills repositories, articles, talks
The engineer builds gamification features on an established iGaming platform: player-facing website, core API, back office. AI agents write most of the code. The engineer owns the plan, the technical decisions and the quality of each merge request.
Tech stack
- Backend: Node.js (Express, Fastify, NestJS), TypeScript, PHP (CodeIgniter 3)
- Frontend: Vue 3 (Pinia, Vite)
- Data and messaging: MySQL, MongoDB, Redis, RabbitMQ, Bull, ClickHouse, PostgreSQL
- Infrastructure: Docker, GitLab CI
- AI tooling: Claude Code (primary), Cursor, MCP
Must have skills
- 4+ years of commercial software development, including 3+ years of backend work in Node.js and TypeScript.
- 1+ year of daily agentic development with Claude Code or a similar tool on real projects: plan mode, subagents, parallel sessions in git worktrees.
- At least one spec-driven approach used on a real project (Superpowers, Spec Kit, OpenSpec, BMAD, Kiro or an in-house process).
- Ability to write and maintain agent context: AGENTS.md or CLAUDE.md, skills, rules, hooks, permissions.
- Solid Vue 3 (Composition API, Pinia). Gamification is player-facing work, so each engineer also builds the UI part of a feature.
- Hands-on MySQL, MongoDB, Redis and message queues (RabbitMQ or Bull).
- Experience with legacy code that has no tests: characterization tests, safe refactoring.
- Understanding of AI development risks: secrets and personal data in agent context, review of AI-written code.
- English at B2 (Upper-Intermediate) or higher.
- Ukranian or russian fluent speaking.
Responsibilities
- Turn product requirements from the product team into specs with acceptance criteria and keep the specs in the repository.
- Deliver each feature through spec, technical plan, task breakdown, implementation and verification. - Keep the agent context for the gamification area current: AGENTS.md, CLAUDE.md, skills, slash commands, subagents, MCP.
- Cover critical paths with tests, including characterization tests around legacy code, so agents can verify their own work.
- Describe the contracts the features depend on (queues, APIs, shared tables) in a machine-readable format.
- Work within the team's quality gates: permissions, hooks, automatic lint, AI-assisted code review in GitLab CI.
- Review AI-written code to the same standard as human-written code. Keep secrets and personal data out of agent context.
- Work across several repositories together with the in-house development team.
Nice to have
- iGaming experience, especially bonus mechanics and player engagement features such as missions, tournaments, leaderboards or loyalty levels. Fintech experience (payments, KYC, provider integrations) also counts. Candidates without domain experience still qualify.
- Product experiments: feature flags, A/B tests, segmentation, retention and conversion metrics.
- Event-driven features built on player events (queues, WebSockets) and integrations with external gamification or CRM services.
- PHP and CodeIgniter 3.
- NestJS, Fastify, ClickHouse, PostgreSQL.
- GitLab CI pipelines and AI-assisted code review in CI.
- Building MCP servers or Claude Code plugins.
- Public examples of AI practice: skills repositories, articles, talks
