GenAI Agentic Trading Research Engineer

Next Frontier Capital; New York (NY); On-site; USD 150,000 - 240,000; Full time

Benefits offered by this job

Comprehensive health care coverage

On-site health and wellness centers

Retirement savings plan

Tuition reimbursement

Mental health support

Financial coaching

Job summary

JPMorgan Chase & Co. seeks an Associate Applied Researcher to build end-to-end agentic systems that convert frontier GenAI capabilities into reliable solutions for client workflows.

You will own problem framing, dataset creation, model/agent design, evaluation, deployment and monitoring in a fast-paced environment. The role combines applied research with production engineering, requiring strong Python coding, LLM experience, and the ability to communicate tradeoffs clearly.

Qualifications

• Strong coding skills with Python and production code ownership.
• Advanced degree in CS/DS/ML or related field.
• Hands-on experience building with LLMs (agent frameworks, tool use, RAG, prompt engineering, evals).
• Understanding of GenAI capabilities, failure modes, and mitigation strategies.
• Proven track record delivering ML/AI systems that moved business metrics.
• Ability to explain technical tradeoffs to non-technical stakeholders.

Responsibilities

• Build end-to-end agentic systems: design, prototype, productionize multi-step LLM agents.
• Drive applied research: evaluate techniques and integrate into production.
• Own the full loop from problem framing to deployment and monitoring.
• Improve quality through evals, error analysis, and feedback loops.
• Partner with sales, quant research, trading, product, and engineering.
• Build and maintain production-grade, observable systems.
• Contribute to technical direction and standards for agent design.

Skills

Python

LLM development

Agent frameworks

Prompt engineering

Model evaluation

Education

Master's degree in Computer Science/Data Science/ML

Job description

JPMorgan Chase & Co. seeks an Associate Applied Researcher to build end-to-end agentic systems that convert frontier GenAI capabilities into reliable solutions for client workflows.

You will own problem framing, dataset creation, model/agent design, evaluation, deployment and monitoring in a fast-paced environment. The role combines applied research with production engineering, requiring strong Python coding, LLM experience, and the ability to communicate tradeoffs clearly.