Staff Applied AI Engineer

Overview

Why Deriv

• We're in production, not planning.
• 400+ users on our internal workflow orchestration platform.
• Open-source Spec-to-PR transforming product specs into full implementations.
• Real money, real regulations: Our AI handles financial transactions and compliance checks.
• You'll join a transformation that's underway, not one waiting for approval.

What You'Ll Do

• Architect scalable solutions: You’ll break down ambiguous, function-wide problems into shippable technical architectures. You won't just solve the immediate bug; you'll design the systems that prevent it.
• Own the outcome: You won’t just build a feature; you’ll ensure it solves the business problem, monitoring it from deployment through to adoption.
• Elevate engineering standards: You’ll review code and design docs not just to catch errors, but to raise the bar for the entire team. You’ll document knowledge so it doesn't stay in your head.
• Bridge the gap: You will facilitate agreement between engineering, compliance, and ops when they all want different things—translating "make it safe" and "make it fast" into "here is the architecture".
• Balance quality and speed: You’ll make strategic calls on technical debt vs. shipping speed, knowing when to hack a prototype and when to engineer a platform.

Who You Are

• You have 7+ years of software engineering experience: At least 3 years building production AI systems. Not prototypes - systems that handle real traffic at scale.
• You’ve shipped production AI: Not notebooks. Not demos. Systems that handle real traffic, break in unexpected ways, and teach you things papers didn't mention.
• You operate across paradigms: You are comfortable with SQL and with prompt engineering. You pick the right tool, not your favourite tool.
• You lead through uncertainty: When the path isn't clear, you facilitate the problem-solving discussions that get the team moving.
• You think in systems: You see the structural flaws behind the symptoms. You don't just optimise code; you optimise how the organisation solves problems.
• Tech stack
• Languages : Python, TypeScript
• AI/ML : OpenAI APIs, Anthropic APIs, LangGraph, Custom ML Pipelines
• Infrastructure : AWS, PostgreSQL, Redis, Docker, LangFuse, Vector Databases, Graph Databases
• The honest reality
• This is demanding work.
• You’ll make decisions with incomplete data and live with the consequences.
• You’ll navigate organisational complexity, convincing stakeholders to change how they work to accommodate the systems you build.
• You’ll balance moving fast with getting it right when real money is at stake.
• But you’ll build systems that actually run.
• You’ll solve problems that matter.
• And you’ll work with people who’ve done this at scale.