Applied AI Engineer, Markets Operations – Associate

JPMorgan Chase JPMorgan Chase · Banking · LONDON, United Kingdom · Commercial & Investment Bank

Applied AI Engineer role focused on building and deploying production-ready AI solutions within JPMorgan Chase's Markets Operations. The role involves hands-on engineering of AI services, data pipelines, and infrastructure, collaborating with various teams to improve workflows and controls. Requires strong Python, API development, and data engineering skills, with a preference for finance/operations AI experience.

What you'd actually do

  1. Contribute to technology and architecture patterns that enable AI solutions across Markets Operations and software engineering use cases
  2. Build and enhance robust, scalable, reusable AI services and supporting infrastructure using modern technologies
  3. Collaborate with AI and data science specialists to design, develop, test, and deploy services integrated with strategic systems and operational processes
  4. Learn Markets Operations processes and apply that knowledge to develop practical solutions and integrations with banking operations systems
  5. Evaluate new AI infrastructure technologies and share findings to inform team technical decisions

Skills

Required

  • Bachelor’s or Master’s degree in Computer Science, Software Engineering, a related field, or equivalent practical experience
  • 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

Nice to have

  • 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

What the JD emphasized

  • production-ready solutions
  • enterprise-grade systems
  • production readiness
  • operational readiness

Other signals

  • production-readiness
  • enterprise-grade systems
  • scalable AI services
  • operational workflows
  • controls
  • productivity
  • Python services
  • APIs
  • data pipelines
  • infrastructure
  • monitoring
  • production readiness
  • domain knowledge
  • workflow pain points
  • durable solutions
  • innovation
  • collaboration
  • engineering excellence
  • technology and architecture patterns
  • AI solutions
  • software engineering use cases
  • robust, scalable, reusable AI services
  • supporting infrastructure
  • modern technologies
  • AI and data science specialists
  • design, develop, test, and deploy services
  • strategic systems
  • operational processes
  • Markets Operations processes
  • practical solutions
  • integrations with banking operations systems
  • Evaluate new AI infrastructure technologies
  • inform team technical decisions
  • Document designs, implementation details, and tradeoffs
  • maintainability
  • knowledge sharing
  • Support scalability, reliability, and security
  • AI and machine learning solutions in production
  • operational readiness and sustainability
  • Partner with operations stakeholders
  • understand workflow pain points
  • translate them into practical technology solutions
  • Bachelor’s or Master’s degree
  • Computer Science, Software Engineering, a related field, or equivalent practical experience
  • strong Python programming skills
  • Design, develop, and integrate RESTful APIs
  • FastAPI
  • Build and support ETL and data pipeline engineering workflows
  • Apply Infrastructure as Code practices
  • Terraform
  • CI/CD pipelines
  • Design and integrate databases and data models
  • Apply monitoring practices
  • understand controls and compliance concepts
  • production environments
  • Communicate effectively in writing and verbally
  • explaining technical concepts to technical and non-technical audiences
  • Collaborate effectively on multi-disciplinary teams
  • incorporate feedback into your work
  • Apply AI and machine learning concepts
  • strong interest in applied AI productization
  • experience from academic work, projects, internships, or roles applying AI in finance, operations, markets, or enterprise technology
  • familiarity with Markets Operations processes
  • trade lifecycle, post-trade operations, reconciliations, controls, or exception management
  • Use AWS
  • MLflow
  • Develop front-end capabilities
  • React or modern front-end development
  • Apply graph database modeling concepts