Senior Lead Software Engineer - Python, Data, AIML, Cloud

JPMorgan Chase & Co.; Greater London; On-site; GBP 90,000 - 120,000; Full time

Job summary

A leading financial institution in Greater London seeks a Senior Lead Software Engineer to design and deliver innovative technology solutions. The candidate will work on Cloud-native data engineering and AI/ML projects, requiring over 10 years of software engineering experience, particularly in Python and Cloud environments. Responsibilities include creating production code, producing architecture artifacts, and contributing to an inclusive team culture. A hands-on engineering role with an emphasis on problem-solving and learning opportunities is crucial.

Qualifications

• 10+ years of experience in applied software engineering.
• Hands-on experience in system design and application development.
• Proficient in coding with Python or similar languages.
• Experience in Cloud-native data engineering solutions.

Responsibilities

• Design and deliver technology products in a secure and stable way.
• Create production code and maintain algorithms.
• Produce architecture for complex applications.
• Build engineering stack for AI/ML products.
• Design data engineering solutions with big data technologies.
• Contribute to software engineering communities.

Skills

Python

Cloud services

Data engineering

Microservices

MLOps

Kubernetes

AWS

Education

Formal training in software engineering concepts

Tools

Docker

ETL services

Job description

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

As a Senior Lead Software Engineer at JPMorgan Chase within the Corporate and Investment Bank Markets Research Technology, 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 Artificial Intelligence/Machine Learning engineering, helping us industrialize AI/ML models at production enterprise 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
• 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 10+ 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, ECS, EKS) 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