At a Glance
- Tasks: Shape the future of Applied AI by creating innovative solutions for Markets Operations.
- Company: Join J.P. Morgan, a global leader in financial services with a focus on creativity and collaboration.
- Benefits: Enjoy competitive pay, mentorship, and opportunities for career growth in a dynamic environment.
- Other info: Be part of a diverse team that values inclusion and continuous learning.
- Why this job: Make a real impact in finance while working with cutting-edge AI technologies.
- Qualifications: Bachelor's or Master's in Computer Science, strong Python skills, and experience with APIs.
The predicted salary is between 70000 - 90000 £ per year.
Help shape the next wave of Applied AI innovation in Markets Operations by turning ideas into production-ready solutions. You will build practical AI capabilities that improve workflows, strengthen controls, and unlock productivity for teams across the organization. Working alongside engineers, AI specialists, and operations partners, you will bridge cutting-edge techniques with enterprise-grade systems.
As an Applied AI Engineer in the applied AI team within Markets Operations, you will design, build, test, and deploy scalable AI services integrated with strategic systems and operational processes. You will collaborate with software engineers, AI and data science specialists, operations stakeholders, and business partners to improve operational workflows, controls, and the software development lifecycle. You will focus on hands-on engineering across Python services, APIs, data pipelines, infrastructure, monitoring, and production readiness. You will build domain knowledge across Markets Operations and translate real workflow pain points into durable solutions. You will contribute to a culture of innovation, collaboration, and engineering excellence.
Job Responsibilities- Contribute to technology and architecture patterns that enable AI solutions across Markets Operations and software engineering use cases.
- Build and enhance robust, scalable, reusable AI services and supporting infrastructure using modern technologies.
- Collaborate with AI and data science specialists to design, develop, test, and deploy services integrated with strategic systems and operational processes.
- Learn Markets Operations processes and apply that knowledge to develop practical solutions and integrations with banking operations systems.
- Evaluate new AI infrastructure technologies and share findings to inform team technical decisions.
- Document designs, implementation details, and tradeoffs to support maintainability and knowledge sharing.
- Support scalability, reliability, and security of AI and machine learning solutions in production, with a focus on operational readiness and sustainability.
- Partner with operations stakeholders to understand workflow pain points and translate them into practical technology solutions.
- Hold a Bachelor's or Master's degree in Computer Science, Software Engineering, a related field, or equivalent practical experience.
- Demonstrate strong Python programming skills.
- Design, develop, and integrate RESTful APIs, such as with FastAPI.
- Build and support ETL and data pipeline engineering workflows.
- Apply Infrastructure as Code practices, such as Terraform, and work within CI/CD pipelines.
- Design and integrate databases and data models.
- Apply monitoring practices and understand controls and compliance concepts in production environments.
- Communicate effectively in writing and verbally, explaining technical concepts to technical and non-technical audiences.
- Collaborate effectively on multi-disciplinary teams and incorporate feedback into your work.
- Apply AI and machine learning concepts with a strong interest in applied AI productization.
- Bring experience from academic work, projects, internships, or roles applying AI in finance, operations, markets, or enterprise technology.
- Demonstrate familiarity with Markets Operations processes such as trade lifecycle, post-trade operations, reconciliations, controls, or exception management.
- Use AWS and tools such as MLflow.
- Develop front-end capabilities with React or modern front-end development.
- Apply graph database modeling concepts.
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.
Applied AI Engineer, Markets Operations - Associate in London employer: J.P. Morgan
As a leading global financial institution, we pride ourselves on fostering a dynamic and inclusive work environment that empowers our employees to excel. The Head of Markets Tax Operations role offers unparalleled opportunities for professional growth, collaboration across diverse teams, and the chance to drive innovation in tax operations while working in vibrant locations like Spain, Italy, and Hungary. Join us to be part of a culture that values excellence, embraces technology, and prioritises employee development, ensuring you can make a meaningful impact in your career.
StudySmarter Expert Advice🤫
We think this is how you could land Applied AI Engineer, Markets Operations - Associate in London
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We think you need these skills to ace Applied AI Engineer, Markets Operations - Associate in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at J.P. Morgan. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
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✨Brush Up on Your Statistics
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✨Get Comfortable with Python and R
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✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
