AI Engineering Lead – Greenfield AI Initiative at Top Macro Fund

This role owns the build-out of internal, bespoke AI systems across the firm's front, middle, and back office: tools that touch research workflows, risk monitoring, trade support, and operations. Unlike a vendor-driven AI rollout, this person is responsible for the firm's actual AI capability from the ground up. If these systems are built well, they compound productivity across every desk in the firm; if built poorly, they become shelfware that nobody trusts.What You'll DoLead design and delivery of internal AI applications spanning research, trading support, risk, and operationsBuild and manage a small applied AI engineering teamPartner directly with heads of desk, risk, and operations to identify high-value AI use casesOwn the full lifecycle from prototype to production, including evaluation, deployment, and monitoring of LLM-based systemsSet technical standards for how AI systems are built, tested, and governed internallyReport on AI initiative progress and roadmap directly to firm leadershipMust-HavesProven track record shipping production AI or LLM-based systems, not just research prototypes. This is non-negotiable for the roleExperience leading an engineering or applied ML teamStrong hands-on background with modern LLM architectures, RAG systems, and evaluation methodsDemonstrated ability to work directly with non-technical business stakeholders across multiple functionsStrong software engineering fundamentals in Python and production ML infrastructureNice-to-HavesPrior experience in financial services or another regulated industryFamiliarity with front, middle, and back office workflows at a trading or asset management firmExperience building AI governance or evaluation frameworksBackground straddling both research and engineering leadershipWhy This RoleThis is a highly visible, high-autonomy mandate: the firm is building its internal AI capability essentially from scratch, and this person will define what it looks like. Compensation is top of market. The team is small by design, with direct access to senior leadership and no bureaucracy standing between an idea and its rollout across the firm. For an AI leader who wants to build the operating system for how a firm actually works, this is that.