Quant Platform Engineer

Description

This is a Quant Platform Engineer role in the PGIM Credit Technology team, based in London with a hybrid work pattern.

The company is the global asset management arm of a US financial group, with nearly US$1.5 trillion in assets under management as of 30 September 2025, offices in 19 countries, and a history of 150 years.

It invests across public and private fixed income, equities, real estate and alternatives, and takes a long-term view on both investments and staff development.

The company is not affiliated with Prudential plc, which is headquartered in the United Kingdom.

The team is a diversity-focused employer with a stated commitment to inclusion.

Responsibilities

• Build and improve the platforms, tools and data infrastructure used by the Quantitative Modelling and Strategies (QMS) organization.
• Design and develop scalable platforms, services and data infrastructure so quant teams can build and run investment analytics.
• Using Python, design and build platform capabilities, services and developer tooling.
• Build and maintain data platforms, quantitative libraries, distributed computing infrastructure and shared services for QMS researchers and investment teams.
• Work with quantitative researchers and technology teams to make sure the platform fits business needs.
• Contribute to architecture, code reviews, testing, performance work and day-to-day operational quality.
• Find ways to improve through automation, new ideas and sound engineering practice.
• The role suits an engineer who wants to work where technology meets quantitative research, helping QMS teams run analytics more effectively.

Requirements

• A bachelor's degree or higher in Computer Science.
• Experience building and delivering software, analytics or data platforms.
• Strong Python software development skills.
• Experience with data engineering, distributed computing and large-scale data processing.
• Experience working closely with quantitative researchers, investment teams and technology organizations.
• An understanding of fixed income, credit, asset management or wider financial markets.
• Strong analytical, problem-solving and communication skills, a collaborative approach, and a focus on business impact.
• Nice to have: experience building quantitative analytics, risk management, portfolio management, investment research or quant platforms.
• Nice to have: experience with distributed computing and data processing frameworks such as Ray, Dask, Apache Spark, Apache Beam or similar.
• Nice to have: experience with event-driven architectures and messaging platforms such as Kafka, RabbitMQ or similar.
• Nice to have: experience with modern engineering practices, including monorepos, CI/CD, automated testing and Python developer tooling.

Conditions

Based in London, with a hybrid work model.

The company welcomes applications from people who do not meet every requirement, and encourages you to apply if your skills fit the role.

The company is a Disability Confident Level 1 employer, committed to an inclusive and accessible workplace for disabled people.

Benefits

• Private medical insurance, with the company paying the full premium for all employees.
• Annual leave of 25 to 28 days at full pay, depending on years of service.
• Retirement savings plan: the company contributes 10% of basic annual salary, and matches employee contributions up to a maximum of 5% of basic annual salary.
• Life assurance of 8 times basic annual salary, up to a maximum benefit of £1.8 million.
• Income protection of 60% of basic annual salary for a limited payment term of 5 years, followed by a capital sum of 2 times basic annual salary at the end of that term.