Applied AI ML Lead- Agentic AI & Python

JPMorgan Chase & Co.; Auchentibber; On-site; GBP 120,000 - 180,000; Full time

Job summary

JPMorgan Chase & Co. is seeking an Applied AI ML Lead - Vice President within IPB Technology AIML to translate business problems into production-grade AI solutions. You will own end-to-end design and delivery of priority IPB AI/ML use cases, focusing on agentic AI, guardrails, and governance across global teams.

You will work with senior stakeholders, drive responsible AI practices, and mentor engineers while advancing client and advisor journeys with scalable ML systems.

Qualifications

• Formal training in software engineering and hands-on experience
• Advanced Python and modern software engineering practices
• Experience with large language models and agentic AI
• Proven delivery of ML systems to production
• Familiarity with governance, model risk, and guardrails

Responsibilities

• Own end-to-end delivery of IPB AI/ML use cases from framing to production
• Lead engineering of agentic AI and LLM-powered products for IPB advisors and clients
• Set engineering quality standards via code reviews and design reviews
• Establish Responsible AI controls in production with observability and risk controls
• Collaborate with IPB stakeholders to surface and fund AI/ML opportunities
• Represent AIML in governance forums and ensure regulatory/data privacy alignment
• Contribute to AI education and mentoring within the team
• Champions diversity, inclusion, and ethical AI practices

Skills

Python proficiency

AI/ML deployment

Communication skills

Software engineering

Hands-on ML

Education

MSc in Computer Science or related

Tools

Claude Code

GitHub Copilot

CI/CD

Docker

Kubernetes

Databricks

Job description

We're looking for a hands-on 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 an Applied AI ML Lead - Vice President 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 AIML in 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 responsibilities

• Owns 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 impact
• Leads the engineering build of agentic AI and LLM-powered products serving IPB advisors and clients across the globe.
• Sets the engineering quality bar for the team's AI products through code reviews, technical design, and pairing with peers and junior engineers
• Establishes and operates Responsible AI controls in production (guardrails, evaluation frameworks, observability, and model risk controls) to firm-wide standards
• Acts as a primary technical partner to IPB business stakeholders, surfacing new AI/ML opportunities and shaping them into funded workstreams
• Represents the AIML team in firm-wide AI/ML governance and engineering forums; ensures cross-border, regulatory, and data-privacy considerations are reflected in solution design
• Contributes to the team's GenAI education programme through training content, knowledge-sharing sessions, and mentoring of junior engineers and interns
• Champions the firm's culture of diversity, Opportunity, inclusion, and respect

Required qualifications, capabilities, and skills

• Formal training or certification in software engineering concepts and expert applied experience
• Advanced 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 to
• Hands-on experience building, evaluating, and deploying machine learning models into production
• Practical experience with Large Language Models, including prompt engineering, RAG, fine-tuning, agentic frameworks, skills.
• Demonstrated experience delivering system design, application development, testing, and operational stability for ML or data-intensive systems
• Strong communication skills with confidence engaging senior business stakeholders and translating technical concepts for non-technical audiences
• Experience applying new methods to determine solutions for complex technology problems across multiple technical disciplines
• MSc in Computer Science, Data Science, Engineering, or a related quantitative field

Preferred qualifications, capabilities, and skills

• Postgraduate-level qualification in data science, artificial intelligence, or machine learning
• Practical experience with CI/CD, containerization, and cloud-native deployment patterns
• Experience within financial services technology, particularly wealth, private banking, or asset management
• Experience with Databricks, Kubernetes, or comparable ML / cloud platforms
• Experience designing or contributing to AI governance, model validation, or guardrail frameworks