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- Tasks: Lead AI innovation to transform customer onboarding and software engineering practices.
- Company: Join J.P. Morgan, a global leader in financial services.
- Benefits: Empower your career with creativity, collaboration, and continuous learning.
- Why this job: Make a real impact in financial services while growing your skills.
- Qualifications: Master’s or Bachelor’s in Computer Science; programming skills in Python and React.
- Other info: Diverse team culture with a focus on innovation and excellence.
The predicted salary is between 36000 - 60000 ÂŁ per year.
Join us at the forefront of Applied AI innovation, where you’ll help shape the next generation of autonomous agents for the world’s largest bank. As a builder, pioneer, and mentor, you’ll bridge the gap between cutting-edge theory and enterprise-grade systems. Collaborate with talented engineers, researchers, and business leaders to deliver impactful solutions. At JPMorgan Chase, you’re empowered to grow your career while making a real difference. Be part of a team that values creativity, collaboration, and continuous learning.
As an Applied Artificial Intelligence Engineering Lead – Vice President in Operations, you will work within an applied AI team dedicated to transforming customer onboarding and software engineering practices. You will partner with software engineers, business stakeholders, and machine learning experts to identify and implement efficiency improvements. Your work will directly impact KYC and onboarding operations, as well as the software development lifecycle. You will also help foster a culture of innovation and excellence.
Job Responsibilities
- Formulate, communicate, and drive implementation of technology and architecture for deploying AI solutions in KYC and onboarding operations and software engineering.
- Build robust, scalable, and reusable AI infrastructure using the latest technologies.
- Collaborate with AI and Data Science specialists to design and deploy services integrated with strategic systems and processes.
- Learn about and understand supported business areas to drive practical solutions and integrations with banking operations systems.
- Conduct comprehensive exploration and analysis of new AI infrastructure technologies to inform long-term strategic technical direction.
- Document and explain rationale and design considerations behind architecture and technology decisions.
- Ensure scalability, reliability, and security of AI/ML solutions in production environments, focusing on long-term sustainability.
Required Qualifications, Capabilities, And Skills
- Master’s or Bachelor’s Degree in Computer Science, Software Engineering, or related field.
- Programming skills in Python and React.
- Experience with RESTful API design, development, and integration (e.g., FastAPI).
- Proficiency in Infrastructure-as-Code solutions using Terraform and CI/CD pipelines.
- ETL and Data Pipeline Engineering expertise.
- Database design, implementation, and integration, including graph database modeling.
- Infrastructure monitoring and compliance knowledge.
- Effective verbal and written communication skills with technical and business audiences.
- Ability to work on multi-disciplinary teams with diverse backgrounds.
Preferred Qualifications, Capabilities, And Skills
- AI or Data Science experience with understanding of fundamental Artificial Intelligence and Machine Learning techniques.
- Research or work experience applying Artificial Intelligence in Finance or Technology.
- Experience with Databricks, MLFlow, Grafana, PySpark.
- Strong presentation, client partnership, stakeholder, and project management skills.
Why Join Us?
Your contributions will help redefine what’s possible in financial services. You’ll be part of a team that values creativity, collaboration, and continuous learning, empowering you to make a real impact and grow your career.
About Us
J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world’s most prominent corporations, governments, wealthy individuals and institutional investors. Our first-class business in a first-class way approach to serving clients drives everything we do. We strive to build trusted, long-term partnerships to help our clients achieve their business objectives.
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs.
About The Team
J.P. Morgan’s Commercial & Investment Bank is a global leader across banking, markets, securities services and payments. Corporations, governments and institutions throughout the world entrust us with their business in more than 100 countries. The Commercial & Investment Bank provides strategic advice, raises capital, manages risk and extends liquidity in markets around the world.
Applied AI ML Lead Engineer - Customer Onboarding and Documentation employer: JPMorganChase
Contact Detail:
JPMorganChase Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Applied AI ML Lead Engineer - Customer Onboarding and Documentation
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those at JPMorgan Chase. A friendly chat can open doors and give you insights that a job description just can't.
✨Tip Number 2
Show off your skills! If you've got a portfolio or projects that highlight your AI and ML expertise, make sure to share them during interviews. It’s a great way to demonstrate your hands-on experience.
✨Tip Number 3
Prepare for technical interviews by brushing up on your Python and RESTful API knowledge. Practice coding challenges and be ready to discuss your thought process – it’s all about showcasing your problem-solving skills!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining our team.
We think you need these skills to ace Applied AI ML Lead Engineer - Customer Onboarding and Documentation
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter for the Applied AI ML Lead Engineer role. Highlight your relevant experience in AI, machine learning, and software engineering, and show how it aligns with our mission at StudySmarter.
Showcase Your Skills: Don’t just list your skills; demonstrate them! Use specific examples from your past work that showcase your programming abilities in Python and React, as well as your experience with RESTful APIs and Infrastructure-as-Code solutions.
Be Clear and Concise: When writing your application, keep it clear and to the point. We appreciate effective communication, so make sure your ideas are easy to understand and directly address how you can contribute to our team.
Apply Through Our Website: We encourage you to apply through our website for a smoother process. This way, your application will be directly reviewed by our hiring team, and you’ll have a better chance of standing out!
How to prepare for a job interview at JPMorganChase
✨Know Your AI Stuff
Make sure you brush up on the latest trends in AI and ML, especially as they relate to customer onboarding and KYC processes. Be ready to discuss how you've applied these technologies in past projects and how they can be leveraged in a banking context.
✨Showcase Your Collaboration Skills
Since this role involves working with diverse teams, prepare examples that highlight your ability to collaborate effectively. Think about times when you partnered with software engineers or business stakeholders to drive a project forward.
✨Prepare for Technical Questions
Expect to dive deep into your technical expertise, particularly around Python, RESTful APIs, and Infrastructure-as-Code. Brush up on your knowledge of Terraform and CI/CD pipelines, and be ready to explain your thought process behind architectural decisions.
✨Communicate Clearly
Effective communication is key, especially when discussing complex AI concepts with non-technical stakeholders. Practice explaining your ideas in simple terms and be prepared to answer questions about your design considerations and the impact of your solutions.
