Job Description

Our client is a pioneer in online trading. They enable customers to trade in the world's financial markets. Focused on customer-centric solutions, they aspire to be the world's leading online trading service provider.

They are seeking an expert to lead the technical implementation of our next generation of agentic systems, creating co-intelligence that collaborates, debates, and decides alongside humans.

Key Responsibilities

• Architect scalable solutions: Youll 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 wont just build a feature; youll ensure it solves the business problem, monitoring it from deployment through to adoption.
• Elevate engineering standards: Youll review code and design docs not just to catch errors, but to raise the bar for the entire team. Youll 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: Youll make strategic calls on technical debt vs. shipping speed, knowing when to hack a prototype and when to engineer a platform.

Key Qualifications

• Programming Languages: Proficiency in Python and TypeScript
• Hands-on experience with OpenAI APIs, Anthropic APIs, LangGraph, and building custom ML pipelines
• Strong experience with AWS, PostgreSQL, Redis, Docker, LangFuse, and modern vector and graph databases
• Proven track record of delivering production-grade AI systems that operate at scale, handle real-world traffic, and perform reliably beyond prototypes and research environments
• Comfortable working across SQL, backend engineering, and prompt engineering, with the ability to select the most effective tools and approaches based on problem context
• Demonstrated ability to lead teams through uncertainty, facilitating structured problem-solving and driving alignment when requirements are unclear