Research Engineer - AI Agents

P2P; Singapore; On-site; SGD 70,000 - 120,000; Full time

Job summary

Jump Trading Group is expanding its engineering-focused group in Singapore, building next-generation AI tools and automation for developers and quantitative researchers. You will work with platform and infrastructure teams to craft robust, agent-enabled tooling used across Jump’s research and trading units.

The role focuses on building and delivering AI-powered applications, integrating LLM APIs, and advancing automation in a fast-paced, research-driven environment.

Qualifications

• 2+ years of professional software engineering or applied AI experience.
• Proficient in Python, with hands-on experience integrating LLM APIs or building AI-powered apps.
• Experience with agent/automation frameworks and developing reliable systems.
• Solid understanding of OS, networking, automation, and core software engineering fundamentals.
• Strong analytical and problem-solving skills focused on developer experience and usability.
• Excellent communication and interpersonal skills; comfortable collaborating across teams.
• Familiarity with Linux and version control tools.

Responsibilities

• Architect, build, and maintain LLM-powered and agent-based tools to streamline developer workflows.
• Collaborate with core platform and infrastructure teams to deliver reliable, scalable solutions.
• Apply best practices in prompt engineering, tool integration, access control, and observability.
• Take ownership from prototyping to deployment, rollout, and documentation.
• Champion modern engineering standards and drive continuous improvement across the tech landscape.
• Other duties as assigned or needed.

Skills

Python

LLM APIs

Agent/Automation

Software engineering

Linux

Tools

Git

CI/CD

Job description

Jump Trading Group is committed to world class research. We empower exceptional talents in Mathematics, Physics, and Computer Science to seek scientific boundaries, push through them, and apply cutting edge research to global financial markets. Our culture is unique. Constant innovation requires fearlessness, creativity, intellectual honesty, and a relentless competitive streak. We believe in winning together and unlocking unique individual talent by incenting collaboration and mutual respect. At Jump, research outcomes drive more than superior risk adjusted returns. We design, develop, and deploy technologies that change our world, fund start-ups across industries, and partner with leading global research organizations and universities to solve problems.

We are growing our engineering-focused group dedicated to building next-generation AI tools and automation for developers and quantitative researchers. This team partners closely with platform and infrastructure engineers to shape robust, agent-enabled tooling used by trading and research groups across Jump.

What You'll Do:

• Architect, build, and maintain LLM-powered and agent-based tools to streamline developer workflows and automate complex tasks
• Collaborate with core platform and infrastructure teams to identify use cases and deliver reliable, scalable solutions
• Apply best practices in prompt engineering, tool/plugin integration, access control, and observability
• Take ownership throughout the product lifecycle, from prototyping to deployment, rollout, and documentation
• Champion modern engineering standards and help drive continuous improvement across Jump's diverse tech landscape
• Other duties as assigned or needed

Skills You'll Need:

• 2+ years of professional software engineering or applied AI experience
• Strong proficiency in Python, with hands-on experience integrating LLM APIs, building AI-powered applications, or working with agent/automation frameworks
• Understanding of operating systems, networking, automation, and core software engineering fundamentals
• Strong analytical and problem-solving skills, focused on developer experience and usability
• Excellent communication and interpersonal skills
• Familiarity with Linux and version control tools
• Reliable and predictable availability

Bonus Points

• Strong opinions on best practices in ML research, tooling, and/or infrastructure
• Experience with end-to-end model development, especially in LLMs
• Prior academic publications and/or contributions to open-source AI research