Quant Data Engineer

Tempest Vane Partners; Greater London; On-site; GBP 90,000 - 130,000; Full time

Job summary

Tempest Vane Partners is seeking an engineer blending quantitative finance, data engineering and AI to design high-throughput data pipelines and AI-enabled tooling for researchers and portfolio managers.

You will work on TB-scale datasets, deploy AI systems, and collaborate with PMs and researchers to uncover alpha opportunities. Expect ownership across architecture and modern AI infrastructure in a demanding, fast-paced environment.

Qualifications

• Proven Python engineering in large-scale production
• Background in data eng, ML or quant eng
• Experience building distributed data pipelines and big datasets
• Commercial AI experience including LLMs and RAG
• Clouds (AWS/GCP/Azure) and Kubernetes
• Strong software engineering practices and production systems
• Excellent communication with stakeholders

Responsibilities

• Design high-throughput data pipelines for quantitative strategies
• Build scalable data platforms for structured and alternative data
• Develop AI-enabled tooling to extract insights from unstructured data
• Deploy and optimize LLMs and ML models in production
• Create backtesting and simulation frameworks to accelerate research
• Collaborate with PMs, researchers, and data scientists on solutions
• Evaluate cutting-edge research in AI and quantitative finance
• Influence architecture across cloud, data and AI infra

Skills

Python (production)

Data engineering

Distributed data pipelines

AI technologies (LLMs, RAG)

Cloud (AWS/GCP/Azure) & Kubernetes

Tools

Spark

Databricks

Airflow

Kafka

KDB

Job description

Our client is a globally recognised investment management firm where technology, data and quantitative research are fundamental to generating investment performance.

As they continue to invest heavily in their systematic and discretionary investment capabilities, they are seeking a Quant Data Engineering & AI Engineer to join a highly collaborative team operating at the intersection of quantitative research, data engineering and Artificial Intelligence.

This is an opportunity to work on some of the industry's most challenging data problems—building large-scale data platforms, developing AI-enabled research tooling and partnering directly with Portfolio Managers to uncover new sources of alpha.

The successful candidate will join a world-class engineering organisation where innovation, experimentation and technical excellence are actively encouraged.

What You'll Get

• Build AI and data platforms used by Quantitative Researchers and Portfolio Managers globally.
• Work on TB-scale datasets spanning structured and unstructured financial data.
• Collaborate directly with investment professionals to identify and develop novel alpha opportunities.
• Design and deploy production AI systems leveraging frontier and open-source models.
• Significant ownership across architecture, engineering and strategic technical initiatives.
• Exposure to large-scale distributed systems, cloud technologies and modern AI infrastructure.
• Competitive compensation, discretionary bonus and an exceptional benefits package.
• The opportunity to work alongside some of the brightest engineers, researchers and investors in the industry.

What You'll Do

• Design and develop high-throughput data pipelines supporting quantitative investment strategies.
• Build and maintain scalable data platforms processing structured and alternative datasets.
• Develop AI-enabled tooling to extract insights from large corpora of unstructured financial information.
• Deploy and optimise LLMs and machine learning models in production environments.
• Engineer robust backtesting and simulation frameworks to accelerate research workflows.
• Partner directly with Portfolio Managers, Quantitative Researchers and Data Scientists to deliver business-critical solutions.
• Evaluate and implement cutting-edge academic and industry research across AI and quantitative finance.
• Contribute to architectural decisions across cloud, data and AI infrastructure.

What You'll Need

• Strong software engineering experience with Python in large-scale production environments.
• A background in Data Engineering, Machine Learning or Quantitative Engineering.
• Experience building distributed data pipelines and working with large datasets.
• Commercial experience with AI technologies, including Large Language Models and RAG architectures.
• Experience with cloud technologies (AWS, GCP or Azure) and Kubernetes.
• Strong understanding of software engineering best practices and production systems.
• Excellent communication skills and the ability to work closely with technical and business stakeholders.

Nice to Have

• Experience within quantitative finance, hedge funds or investment management.
• Knowledge of modern AI tooling (LangGraph, MCP, vLLM, Triton, Fine-Tuning, GraphRAG, etc.).
• Experience with Spark, Databricks, Airflow, Kafka or KDB.
• Familiarity with GPU infrastructure and model optimisation.
• Exposure to systematic trading, alpha research or backtesting frameworks.
• Experience mentoring engineers or leading technical initiatives.

Interested?

This role would suit an engineer who enjoys solving difficult problems at scale and is excited by the opportunity to combine quantitative finance, data engineering and Artificial Intelligence in a high-impact environment.

You'll have the opportunity to work on problems spanning distributed systems, machine learning, alternative data, large language models and alpha generation—all within one of the industry's most technologically advanced investment firms.