01Overview
We're looking for a hands-on senior AI engineer ready to take their career to new heights. Join the ranks of top talent at one of the world's most influential companies.
As Applied AI ML Lead- AI Engineer at JPMorgan Chase within the International Private Bank (IPB) Technology Artificial Intelligence and Machine Learning (AIML) Team, you provide deep engineering expertise and work across agile teams to enhance, build, and deliver trusted market-leading AI products in a secure, stable, and scalable way. You will translate business problems into agentic AI and machine learning solutions, taking models from concept through to production-grade services with measurable client and advisor impact.
You will be responsible to the Head of AI, IPB Tech for the end-to-end design, build, and production delivery of priority IPB AI/ML use cases, with particular focus on agentic AI applications, generative AI guardrails, and production ML supporting advisor and client journeys.
Job ResponsibilitiesOwns end-to-end delivery of priority IPB AI/ML use cases, from problem framing and business case through to deployed, monitored production services with measurable advisor and client impactLeads the engineering build of agentic AI and LLM-powered products serving IPB advisors and clients across international marketsSets the engineering quality bar for the team's AI products through code reviews, technical design, and pairing with peers and junior engineersEstablishes and operates Responsible AI controls in production (guardrails, evaluation frameworks, observability, and model risk controls) to firm-wide standardsActs as a primary technical partner to IPB business stakeholders, surfacing new AI/ML opportunities and shaping them into funded workstreamsRepresents the AIML team in firm-wide AI/ML governance and engineering forums; ensures cross-border, regulatory, and data-privacy considerations are reflected in solution designContributes to the team's GenAI education programme through training content, knowledge-sharing sessions, and mentoring of junior engineers and interns
Required qualifications, capabilities, and skillsFormal training or certification on AI/ML engineering concepts and 5+ years applied experienceAdvanced proficiency in Python and modern software engineering practices (testing, design patterns, code review, version control)Fluent with AI coding tools (e.g., Claude Code, GitHub Copilot) as a core part of day-to-day software development, with the judgement to know when to lean on them and when not toHands-on experience building, evaluating, and deploying machine learning models into productionPractical experience with Large Language Models, including prompt engineering, RAG, fine-tuning, and agentic frameworksPractical experience with CI/CD, containerisation, and cloud-native deployment patternsDemonstrated experience delivering system design, application development, testing, and operational stability for ML or data-intensive systemsStrong communication skills with confidence engaging senior business stakeholders and translating technical concepts for non-technical audiencesExperience applying new methods to determine solutions for complex technology problems across multiple technical disciplinesMaster's degree in Computer Science, Data Science, Engineering, or a related quantitative field (or equivalent applied experience)
Preferred qualifications, capabilities, and skillsIndustry-recognised cloud / GenAI certification (e.g., AWS Certified Generative AI Developer - Professional, or similar)Experience within financial services technology, particularly wealth, private banking, or asset managementExperience with Databricks, Kubernetes, or comparable ML / cloud platformsExperience designing or contributing to AI governance, model validation, or guardrail frameworksFamiliarity with JPM-internal AI/ML infrastructure and governance for internal candidates .
