Skills

Python Java C# Go Scala SQL Data Engineering Docker Kubernetes Monitoring Problem-solving Decision-making Databases Pandas Snowflake Langchain

Job Specifications

Overview

My client is looking for an ambitious and highly motivated AI Engineer to join a lean, elite AI team operating at the intersection of quantitative finance and cutting-edge technology. In this role, you will act as a strategic partner to investment teams, helping to transform their decision-making processes by building scalable data architectures for Generative AI.

This is an embedded position where you will sit directly with the teams you support, gaining first-hand insight into their workflows. You will be responsible for bridging the gap between raw financial data and the firm’s GenAI platform, ensuring models are fed by robust, high-performance data pipelines.

Responsibilities

Designing and building robust, scalable data pipelines and specialized workflows to power AI-driven investment solutions.
Embedding within investment teams to identify opportunities for AI integration, translating complex data challenges into technical realities.
Developing and promoting best practices for data engineering in an AI context, including the creation of shared libraries and feature stores.
Ensuring tangible impact by delivering systems that allow teams to maintain and utilize AI tools autonomously after the initial embedding phase.
Monitoring and optimizing AI data flows, ensuring the reliability and performance of existing systems while identifying enhancements for the core AI platform.

Requirements

Broad technical expertise in data processing and a passion for staying current with the rapidly evolving Generative AI landscape.
A track record of high-value automation, with the ability to identify where data-driven AI can significantly improve business efficiency.
Exceptional interpersonal skills, with a proven ability to collaborate with both technical engineers and non-technical investment professionals.
A methodical approach to problem-solving, particularly when debugging complex, non-deterministic AI data outputs.
Proficiency in modern languages such as Python, C#, Scala, Java, or Go.
Experience with data storage and manipulation tools including SQL, Pandas/Polars, Snowflake, and Vector Databases.
Familiarity with the GenAI ecosystem, including frameworks like LangChain or LlamaIndex and model evaluation tools like MLFlow.
Knowledge of infrastructure and orchestration, specifically Docker, Kubernetes, and data tools like Airflow, Dagster, or DBT.

Benefits

Competitive salary and performance-based bonus opportunities.
A collaborative, flat structure with a culture of constant learning and modern tech.
Direct exposure to the front-office environment and the firm's bottom line.
Smart offices, free food, and a commitment to professional skill development.

About the Company

We are a specialist technology recruiting firm dedicated to connecting the brightest and best STEM talent into the most exciting opportunities across the world’s most renowned scientific-led quantitative hedge funds, proprietary trading firms and high-growth start-ups. As an organisation, we seek to combine our 20+ years of human expertise in tech recruiting best practice alongside a data-led research-driven methodology to unearth, connect and engage with the most exceptional calibre of technology talent across the industry.... Know more