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Software Engineer III – Python, Data, Cloud, AIML

J.P. Morgan

London

On-site

GBP 60,000 - 90,000

Full time

Today
Be an early applicant

Job summary

A global financial services firm in London seeks a Software Engineer III to enhance technology products leveraging Cloud-native and AI/ML engineering. This role involves hands-on coding and collaboration within agile teams to tackle technical challenges. Candidates should have proficiency in Python, experience in microservices, and a solid background in data engineering. Join a diverse culture that supports professional growth.

Qualifications

  • Proficient in coding in Python or other languages.
  • Experience in application development and operational stability.
  • Knowledgeable in microservices and data-intensive applications.

Responsibilities

  • Design and deliver stable technology products.
  • Develop secure, high-quality production code.
  • Collaborate with agile teams to resolve complex challenges.

Skills

Python
Software Development Life Cycle
Cloud-native solutions
Data engineering
Microservices
Problem-solving

Education

Formal training in software engineering

Tools

AWS
Docker
Kubernetes
Spark
Job description

Join us and take your software engineering career to new heights, working on cutting-edge technology in a collaborative environment. You’ll have the opportunity to design and deliver market-leading products, leveraging Cloud-native and AI/ML engineering. We value your creativity, problem-solving skills, and passion for learning. Be part of a team that celebrates diversity, equity, and inclusion, and supports your professional growth. Your contributions will help shape the future of financial technology.

As a Software Engineer III at JPMorgan Chase as a part of the Markets Research Technology team, you will be responsible for designing and delivering secure, stable, and scalable technology products. Your role will involve hands-on work across data engineering, backend development, and AI/ML engineering, with a focus on industrializing models at a production scale. You will collaborate with agile teams to tackle complex technical challenges and support the firm's business objectives. Your contributions will have a direct impact on our technology stack and foster innovation within our team culture.

Job Responsibilities
  • Execute software solutions, design, development, and technical troubleshooting
  • Create secure, high-quality production code and maintain algorithms
  • Produce architecture and design artifacts for complex applications
  • Build engineering stack for Data and AIML products, including Cloud infrastructure, DevOps, and MLOps
  • Design and implement data engineering solutions using modern big data technologies
  • Contribute to software engineering communities of practice and technology events
  • Foster a team culture of diversity, opportunity, inclusion, and respect
  • Embrace learning, problem-solving, creative thinking, and a can-do attitude
Required Qualifications, Capabilities, and Skills
  • Formal training or certification on software engineering concepts and proficient applied experience
  • Hands-on experience in system design, application development, testing, and operational stability
  • Proficient in coding in one or more languages, including Python
  • Experience developing, debugging, and maintaining code in large environments
  • Knowledge of the Software Development Life Cycle
  • Proven ability in system design, microservices, distributed systems, and data-intensive applications
  • Experience with Cloud services, Infrastructure as Code, containerized application development, and big data technologies
  • Practical experience developing production-scale Cloud-native data engineering solutions
  • Familiarity with Cloud Data engineering services and MLOps
  • Ability to convey design choices and communicate effectively with stakeholders
Preferred Qualifications, Capabilities, and Skills
  • Experience with data and application migration to AWS
  • Experience working on recommendation systems or other AI/ML systems
  • Practical experience with Kubernetes, EKS, Docker, MLOps, and Spark
  • Prior experience collaborating with data scientists
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