Lead Software Engineer - MLOps

Testing Site - JPMC; Greater London; On-site; GBP 90,000 - 140,000; Full time

Job summary

JPMorgan Chase leads digital banking innovation and is shaping the future of financial services with AI/ML. As Lead Software Engineer in the International Consumer Bank MLOps team, you will design, build, and deploy scalable AI/ML solutions that empower data scientists and product teams to deliver secure, customer-focused systems.

You will collaborate across engineering and product disciplines to translate business initiatives into robust services, ensuring high reliability, security, and

Qualifications

• Formal training or certification on software engineering concepts.
• Recent hands-on experience as a back-end software engineer, especially with customer-facing, LLM-powered microservices.
• Proficiency in Java and Python programming languages.
• Experience designing and implementing effective tests (unit, component, integration, end-to-end, performance).
• Excellent written and verbal communication skills in English.
• Familiarity with advanced AI/ML concepts and protocols, such as Retrieval-Augmented Generation, agentic system architectures, and Model Context Protocol.
• Strong interest in building generative AI applications and tooling.
• Experience with cloud technologies, distributed systems, RESTful APIs, and web technologies.
• Understanding of event-based architecture, data streaming, and messaging frameworks.
• Proficiency in operating, supporting, and securing mission-critical software applications.
• Understanding of various data stores (relational, non-relational, vector).
• Ability to mentor team members on coding practices, design principles, and implementation patterns.
• Ability to manage stakeholders and prioritize deliverables across multiple work streams.

Responsibilities

• Deliver end-to-end cloud-native microservices and data pipelines using modern technologies and best practices.
• Structure software for clarity, testability, and ease of evolution.
• Build scalable solutions that avoid single points of failure.
• Develop secure code to protect customers and the organization.
• Investigate and resolve issues promptly to prevent recurrence.
• Ensure zero-downtime releases for end-users.
• Monitor model and system performance, identifying and solving problems effectively.
• Build reliable, easy-to-operate systems.
• Continuously update and upgrade technologies and patterns.
• Maintain and improve deployed AI/ML models and microservices throughout the software development lifecycle, including production and incident management.
• Ensure compliance and security in AI/ML solution deployment and operation.

Skills

Java

Python

LLM microservices

Cloud technologies

RESTful APIs

Data streaming

Mentoring

Stakeholder management

English communication

Distributed systems

Education

Bachelor's degree in Computer Science

Tools

MLflow

SageMaker

Databricks

BentoML

Arize

AWS

Job description

Join us as we transform digital banking and redefine what’s possible for our customers. You’ll have the opportunity to shape the future of financial services, working with cutting-edge technology and a diverse, collaborative team. At JPMorganChase, your curiosity and passion for technology will help us deliver secure, intelligent banking solutions. We value your ideas and empower you to make a real impact. Discover career growth and mobility while building the bank of the future.

Job Summary

As a Lead Software Engineer at JPMorgan Chase within the International Consumer Bank MLOps team, you will design, build, and deploy scalable AI/ML solutions that promote innovation and deliver outstanding banking experiences. You will collaborate with data scientists, product managers, and engineering teams to translate business initiatives into robust, customer-focused systems. Your work will enable us to leverage foundational AI and machine learning models to enhance our services. You will be part of a diverse, inclusive, and geographically distributed team, focused on delivering secure and intelligent banking.

Job Responsibilities

• Deliver end-to-end cloud-native microservices and data pipelines using modern technologies and best practices
• Structure software for clarity, testability, and ease of evolution
• Build scalable solutions that avoid single points of failure
• Develop secure code to protect customers and the organization
• Investigate and resolve issues promptly to prevent recurrence
• Ensure zero-downtime releases for end-users
• Monitor model and system performance, identifying and solving problems effectively
• Build reliable, easy-to-operate systems
• Continuously update and upgrade technologies and patterns
• Maintain and improve deployed AI/ML models and microservices throughout the software development lifecycle, including production and incident management
• Ensure compliance and security in AI/ML solution deployment and operation

Required Qualifications, Capabilities, and Skills

• Formal training or certification on software engineering concepts and proficient advanced experience.
• Recent hands-on experience as a back-end software engineer, especially with customer-facing, LLM-powered microservices
• Proficiency in Java and Python programming languages
• Experience designing and implementing effective tests (unit, component, integration, end-to-end, performance)
• Excellent written and verbal communication skills in English
• Familiarity with advanced AI/ML concepts and protocols, such as Retrieval-Augmented Generation, agentic system architectures, and Model Context Protocol
• Strong interest in building generative AI applications and tooling
• Experience with cloud technologies, distributed systems, RESTful APIs, and web technologies
• Understanding of event-based architecture, data streaming, and messaging frameworks
• Proficiency in operating, supporting, and securing mission-critical software applications
• Understanding of various data stores (relational, non-relational, vector)
• Ability to mentor team members on coding practices, design principles, and implementation patterns
• Ability to manage stakeholders and prioritize deliverables across multiple work streams

Preferred Qualifications, Capabilities, and Skills

• Background in STEM with exposure to productionising machine learning systems
• Experience with MLOps tools and platforms (e.g., MLflow, Amazon SageMaker, Databricks, BentoML, Arize)
• Proficiency in cloud-native microservices architecture
• Hands-on experience with Amazon Web Services (AWS)
• Previous experience as a Platform engineer
• Experience working in highly regulated environments or industries

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