Senior AI Engineer
The Firm & Role
Our client is a premier global alternative investment manager with over $80bn AUM. For over two decades, they have operated at the intersection of technology and finance, pioneering proprietary "Alpha Capture" applications and systematic strategies.
As a Lead AI Engineer, you will join an expanding, high-octane AI unit. This is a senior-level appointment designed for an engineer who thrives on solving complex business problems by bridging the gap between Large Language Models (LLMs) and production-grade financial systems. You will be instrumental in identifying high-value AI opportunities and driving the firm’s technical growth.
Key Responsibilities
- Architect & Scale: Lead the design, development, and maintenance of Python web services on Kubernetes, integrating LLMs from external providers and deploying open-source models internally.
- Core Asset Development: Build and own the robust, scalable APIs and core data assets that are vended to the entire organization.
- Technical Mentorship: Act as a subject matter expert, educating and upskilling other engineers across the firm on AI techniques and best practices.
- Strategic Collaboration: Partner with developers and business users to translate high-level needs into functional, high-profile software solutions with cross-company impact.
- Innovation Leadership: Drive a culture of continuous improvement, ensuring the firm remains at the cutting edge of AI implementation in the hedge fund space.
Requirements
- Senior Expertise: 7+ years of professional software engineering experience with a track record of owning business-critical systems.
- Python Mastery: Expert-level proficiency in Python and experience managing high-availability APIs in production.
- Applied AI: At least 2 years of experience applying LLMs in an industrial/commercial setting (beyond personal projects).
- Infrastructure & Data: Deep knowledge of deploying services in Kubernetes and a strong background in data engineering or data modeling.
- Communication: Proven ability to deliver AI-driven outputs to non-technical users and stakeholders.