Software Engineer III - Python, AI/ML, Data, Cloud

JPMorgan Chase & Co.; Greater London; On-site; GBP 80,000 - 100,000; Full time

Job summary

A leading financial services firm is seeking a Software Engineer III to develop and implement innovative technology solutions in their Corporate and Investment Bank Markets Research Technology team. This hands-on role requires 5+ years of experience in software engineering and knowledge of cloud-native data engineering, Python programming, and modern big data technologies. Join a collaborative environment that values diversity and innovation, contributing to impactful projects in AI/ML engineering.

Qualifications

• 5+ years of proficient applied experience in software engineering.
• Hands-on experience in system design, application development, testing.
• Experience with Cloud-native data engineering solutions.

Responsibilities

• Designs and implements data engineering solutions, leveraging modern big data technologies.
• Builds engineering stack required for Data and AIML products.
• Creates secure and high-quality production code.

Skills

Software engineering concepts

Python

System design

Cloud services

Microservices

Data engineering

MLOps

Tools

AWS

Kubernetes

Docker

Terraform

ETL

Job description

We have an exciting and rewarding opportunity for you to take your software engineering career to the next level.

As a Software Engineer III at JPMorgan Chase within the Corporate and Investment Bank Markets Research Technology, you will be an experienced member of an agile team, tasked with designing and delivering reliable, market-leading technology products in a secure, stable, and scalable manner. Your responsibilities include implementing critical technology solutions across various technical domains to support the firm's business objectives. You will engage in challenging projects involving Cloud-native data, backend engineering, and AI/ML engineering, contributing to the industrialization of AI/ML models at a production scale. This position is a hands‑on engineering role, where experience with data science or machine learning modeling is beneficial but not mandatory.

Job responsibilities

• Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
• Creates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systems
• Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development
• Builds engineering stack required for Data and AIML products, including data engineering, backend engineering, Cloud infra DevOps and MLOps
• Designs and implements data engineering solutions, leveraging modern big data technologies
• Contributes to software engineering communities of practice and events that explore new and emerging technologies
• Adds to team culture of diversity, opportunity, inclusion, and respect
• Embraces a passion for learning, problem-solving, creative thinking and a can-do attitude.

Required qualifications, capabilities, and skills

• Formal training or certification onsoftware engineeringconcepts and 5+ years proficient applied experience
• Hands‑on practical experience in system design, application development, testing, and operational stability
• Proficient in coding in one or more languages (Python preferably)
• Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages
• Overall knowledge of the Software Development Life Cycle
• Proven track record in system design, architecting and developing microservices, distributed systems and data-intensive applications
• Experience with Cloud services, Infrastructure as Code, containerized application development, big data and modern data engineering technologies
• Practical experience developing Production‑scale Cloud‑native data engineering solutions in commercial environments
• Familiarity with Cloud Data engineering services (e.g., ETL, Glue, S3, Athena) and MLOps
• Ability to convey design choices and results clearly and communicate effectively to stakeholders of various backgrounds

Preferred qualifications, capabilities, and skills

• Experience with data, AWS and AIML engineering in commercial settings
• Experience working on Production scale AI/ML systems
• Practical experience with Kubernetes, EKS, Docker, Terraform, MLOps
• Prior exposure to LLMs, RAG, OpenSearch and vector databases
• Prior experience collaborating with data scientists