AI Engineer

FTMO, Prague office

Overview

FTMO is the prop firm traders trust. OANDA is a regulated global broker, now part of the FTMO group. Both run on software that has to be fast, correct and compliant, and we want AI-first delivery to be how that software gets built.

This role sits in the AI Team, a small senior team reporting to the AI Lead, and serves the whole of FTMO & OANDA, engineering and business alike. It works closely with the team leads, product teams, infrastructure and security to turn AI-native delivery from a set of experiments into the default way the group ships.

AI moves faster than any roadmap, so most of what this team takes on has no playbook. Nobody has solved it before, at least not here and often not anywhere. The problem defines the work, not the job title. You learn the domain fast, find the real problem, ship something that works, and hand it over so the team owns the result.

What you need

Proven record of shipping and owning production software across the full lifecycle.
Staff-level scope: you've led cross-team technical work with no playbook, set a direction others followed, and made decisions that held up.
You learn unfamiliar domains fast: has walked into a business area they knew nothing about and shipped something its people actually use.
You thrive on ambiguity and context switching: frames the problem and drives it to done without a spec or a product manager.
Strong general engineering: you read, design and review production code in at least one major stack, and reason about architecture, testing and security even when an agent writes the lines.
Solid knowledge of IT system architectures and principles, and current with AI architecture patterns.
Understanding of where AI fails and how agents can introduce security vulnerabilities into the SDLC.
Previous AI-first role, with recent work where you wrote little to no code by hand and still shipped top-grade results.
Deep, practical fluency with agentic coding tools and harnesses (Claude Code and the Claude Agent SDK, Codex, Cursor or equivalents): context management, compaction, long-running sessions and multi-agent patterns.
You've built agent scaffolding: AGENTS.md http://AGENTS.md and CLAUDE.md http://CLAUDE.md conventions, init scripts, progress and checkpoint files, feature lists, and end-to-end test loops.
MCP and tool integration: you wire agents safely to internal systems, APIs, repositories, logging and CI.
Evals and quality: you design eval suites and verification loops so agent output is measured against tests, latency and style, not vibes.
AI infrastructure: model routing and access, sandboxes, permissioning and secrets, observability and cost control for agent runs.
Prompt and context engineering as an everyday discipline.
Ownership, teaching and influence: you take problems from proof of concept to production, and get other engineers to adopt new ways of working without a mandate.
Clear communication: you can explain a delegate / review / own boundary to a skeptical senior engineer and a team lead, and convince both.
Pragmatism: you know what to delegate to an agent, what to review and what to own.
English language at C1 level or above.

AI Engineer

Overview

AI Engineer

Overview

What you need

Nice to have

Build the platform

Ambassador AI in new teams

Solve new problems across the business

Set direction

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FTMO