Lead Software Engineer - Python, Data, Cloud, AIML

JPMorgan Chase & Co.; Greater London; On-site; GBP 90,000 - 130,000; Full time

Job summary

JPMorgan Chase & Co. in London seeks an experienced Lead Software Engineer to drive cloud-native data, backend engineering and AIML initiatives.

You will shape secure, scalable software across multiple tech areas, contributing to production-scale AI/ML workflows while mentoring an agile team. Ideal candidates have strong system design, microservices and data engineering skills, plus hands-on coding with Python and cloud technologies in a financial setting.

Qualifications

• Formal training or certification in software engineering concepts.
• Hands-on experience in system design, development, testing and operations.
• Proficient in Python and modern programming languages.
• Experience with cloud services, IaC, containers, big data and data engineering.
• Proven track record in microservices and data-intensive applications.

Responsibilities

• Executes software solutions with production-grade, secure code.
• Creates architecture and design artifacts for complex apps and ensures constraints.
• Builds data and AIML pipelines including Cloud infra DevOps and MLOps.
• Designs data engineering solutions using modern big data tech.
• Collaborates with data scientists and stakeholders to convey design choices.

Skills

Python

Cloud architecture

Microservices

Data engineering

DevOps / MLOps

Big data

SQL

System design

Education

Formal training or certification in software engineering concepts

Tools

AWS

Kubernetes

Docker

OpenSearch

Knowledge graphs

Job description

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

As a Lead Software Engineer at JPMorgan Chase within theCommercial & Investment Bank's Markets Research Technologyteam,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. You will work on challenging Cloud-native data, backend engineering and AIML engineering,helping usindustrialize AI/ML models at Production scale. This role is a technical hands-on Engineering role. Experience with data science/ML modeling is advantageous but not essential to this role.

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

• 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 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

• 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 stack

• 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, preferably in financial sector

• Experience working on recommendation systems, LLM applications or other AI/ML systems

• Practical experience with Kubernetes, EKS, Docker, MLOps

• Prior exposure to LLMs, RAG, Knowledge Graph Technologies, OpenSearch and vector databases

• Prior experience collaborating with data scientists