Software Engineer III – Python, AIML, AWS, EKS in London

Software Engineer III – Python, AIML, AWS, EKS in London

London Full-Time 63000 - 77000 £ / year (est.) No working from home possible
JPMorganChase

At a Glance

  • Tasks: Engineer and deploy innovative ML solutions using Python and AWS.
  • Company: Join J.P. Morgan's dynamic Applied AI/ML Software Engineering team.
  • Benefits: Competitive salary, health benefits, and opportunities for continuous learning.
  • Other info: Collaborative environment with excellent career growth and agile practices.
  • Why this job: Make a real impact in the world of machine learning and technology.
  • Qualifications: Bachelor’s degree in Computer Science or related field; Python experience required.

The predicted salary is between 63000 - 77000 £ per year.

J.P. Morgan is seeking a Software Engineer with expertise in AWS and Python, and a passion for Machine Learning, to help engineer and deploy innovative ML solutions into production. You will join the Applied AI/ML Software Engineering team, collaborating with technology teams across the firm, contributing to both new and ongoing projects. As a Software Engineer III at JPMorganChase within the CIB Security Services Technology Applied AIML team, you serve as a seasoned member of an agile team to design and deliver trusted market-leading technology products in a secure, stable, and scalable way. You are responsible for carrying out critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.

In this role, you will work alongside Data Scientists to build cloud-based frameworks for hosting machine learning models, providing software engineering expertise throughout the model development lifecycle. You will leverage both internal and external cloud platforms, utilizing proprietary and open-source tools to ensure models meet SDLC standards, are production-ready, and can be deployed efficiently. The position requires close interaction with platform developers, engineering communities, and the integration of existing and new technologies.

Job Responsibilities
  • Develop and maintain high-quality, secure applications using Python and AWS
  • Create architecture and design deliverables
  • Integrate AIML solutions into complex, domain-specific operations processing systems
  • Participate in code reviews, design discussions, and agile planning sessions
  • Collaborate with SRE and production monitoring teams to ensure system reliability and performance
  • Contribute to software engineering communities of practice and technology events
  • Embrace continuous learning, creative problem-solving, and a can-do attitude
Required Qualifications, Capabilities, and Skills
  • Bachelor’s degree or higher in Computer Science, Engineering, or a related field, or equivalent formal training/certification
  • Proven hands-on experience in Python application development
  • Proven hands-on experience developing, debugging and maintaining production applications
  • Solid understanding of software development best practices, including version control, testing, and CI/CD
  • Strong problem-solving, communication, and collaboration skills, with the ability to convey design choices and communicate effectively with stakeholders
  • Familiarity with Machine Learning Operations (MLOps)
  • Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, test creation, troubleshooting, or documentation) with demonstrated ability to critically evaluate, validate, and refine AI-generated outputs for correctness, performance, and security.
  • Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage within team practices.
Preferred Qualifications, Capabilities, and Skills
  • Experience with Cloud services, Infrastructure as Code (IaC) and containerized application development
  • Familiarity with relational databases (e.g., Postgres) and AWS services such as S3, EKS, SageMaker, and Bedrock
  • Practical experience with Kubernetes, EKS, Docker, Kafka, MLOps and Large Language Model Operations (LLMOps)
  • Experience working on AIML systems and/or prior experience collaborating with data scientists

Software Engineer III – Python, AIML, AWS, EKS in London employer: JPMorganChase

JPMorganChase is an exceptional employer, offering a dynamic work environment in Greater London where innovation thrives. With a strong commitment to diversity and inclusion, employees benefit from collaborative agile teams, extensive professional development opportunities, and the chance to work on cutting-edge technology products that shape the future of finance. Join us to be part of a culture that values your contributions and supports your growth.

JPMorganChase

Contact Details:

JPMorganChase Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Software Engineer III – Python, AIML, AWS, EKS in London

Join Local Tech Meetups

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Contribute to Open Source Projects

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We think you need these skills to ace Software Engineer III – Python, AIML, AWS, EKS in London

Python
AWS
Machine Learning
MLOps
Software Development Best Practices
Version Control
CI/CD

Some tips for your application 🫡

Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.

Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at JPMorganChase.

Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at JPMorganChase and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!

Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!

How to prepare for a job interview at JPMorganChase

Brush Up on Your Coding Skills

For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.

Know Your Tools and Frameworks

Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If JPMorganChase uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.

Showcase Your Projects

Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.

Prepare for Behavioural Questions

While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.