Applied AI ML Associate - Agentic AI and Python

JPMorgan Chase JPMorgan Chase · Banking · GLASGOW, LANARKSHIRE, United Kingdom · Asset & Wealth Management

Associate-level Applied AI ML Engineer focused on designing, developing, and delivering components of agentic AI and machine learning products for the International Private Bank. The role involves writing production code, building features for agentic AI and LLM applications, and contributing to model evaluation and responsible AI standards.

What you'd actually do

  1. Executes standard software solutions, design, development, and technical troubleshooting for the team's AI/ML products
  2. Builds and tests features of agentic AI, LLM-powered and ML applications under the direction of senior engineers
  3. Writes secure, high-quality production code and maintains algorithms that run synchronously with appropriate systems
  4. Contributes to model evaluation, guardrail testing, and observability tasks to firm-wide Responsible AI standards
  5. Participates in agile ceremonies, code reviews, and technical design discussions

Skills

Required

  • Formal training or certification on AI/ML engineering concepts and applied experience
  • Proficiency in Python and a working grasp of modern software engineering practices (testing, version control, code review)
  • Practical exposure to machine learning and/or Large Language Models (prompt engineering, RAG, or agentic frameworks) through study, projects, or work experience
  • Familiarity with AI coding tools as part of the development workflow
  • Understanding of CI/CD, containerisation, or cloud-native deployment concepts
  • Ability to communicate technical concepts clearly to teammates and stakeholders
  • BSc in Computer Science, Data Science, Engineering, or a related quantitative field

Nice to have

  • Industry-recognised cloud / GenAI certification (e.g., AWS Certified Generative AI Developer - Professional, or similar)
  • Experience building or deploying an ML or LLM-powered application (academic, internship, or professional)
  • Exposure to financial services technology
  • Familiarity with Databricks, Kubernetes, or comparable ML / cloud platforms
  • Familiarity with JPM-internal AI/ML infrastructure and governance for internal candidates

What the JD emphasized

  • agentic AI
  • LLM-powered

Other signals

  • agentic AI
  • LLM-powered applications
  • production-quality code