Level

Jump Trading

Research Engineer – AI Agents

AI in this role

prompt-engineeringai-agentsai-research

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

How we rate this

Research Engineer – AI Agents at Jump Trading rates 87 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

Prompt EngineeringAI AgentsAI Research

Questions you could be asked

  1. How do you structure and test a prompt to get consistent output from a language model?
  2. How do you decide when an AI agent can act on its own versus asking for approval first?
  3. Tell me about a research question you investigated. What did you find?
  4. How would you decide a model or AI system is ready to ship?
  5. Tell me about a time a model underperformed in production. How did you find out, and what did you change?

Adapt your resume

  • List these exact terms on your resume: Prompt Engineering, AI Agents, and AI Research. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.

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