Senior Lead Software Engineer - Python, Data, Cloud, AI/ML

JP Morgan Chase; Greater London; On-site; GBP 62,000 - 102,000; Full time

Job summary

JPMorgan Chase in London seeks a senior software engineer to design, build, and maintain cloud‑native data, backend, and AI/ML solutions that support our financial services objectives. You will work on microservices, data pipelines, ELT processes, and large language model applications, collaborating with data scientists to validate outputs and ensure security and resilience.

This role offers hands‑on ownership in a highly technical environment, with a focus on production‑scale systems,

Qualifications

• Formal training or certification in software engineering concepts with applied experience.
• Hands-on practical experience in system design, development, testing, and stability.
• Proficiency in Python and modern programming languages.
• Experience in large corporate environments with databases and querying languages.
• Strong knowledge of the SDLC.
• Proven track record in microservices, distributed systems, and data-intensive apps.
• Experience with cloud services, IaC, containers, big data, and data engineering tech.
• Production-scale cloud-native data engineering experience.
• Familiarity with ETL, Glue, S3, Athena, and MLOps.
• Experience leading AI-assisted development tools with validation for correctness, performance, security.
• Responsible AI practices in engineering workflows.
• Ability to communicate design choices clearly to stakeholders.
• Experience with data, AWS, and AI/ML in commercial (financial) settings.
• Experience with AI/ML systems / recommendation systems.
• Kubernetes, EKS, Docker, and MLOps experience.
• Exposure to LLMs, RAG, knowledge graphs, OpenSearch, vector DBs.
• Experience collaborating with data scientists.

Responsibilities

• Execute software solutions, design, develop, and troubleshoot complex problems.
• Create secure, production-grade code and maintain production algorithms.
• Produce architecture and design artifacts for complex applications.
• Build data and AI/ML stack including data engineering, backend, cloud DevOps, and MLOps.
• Design and implement data engineering solutions with modern big data tech.
• Drive adoption and governance of AI-assisted engineering practices.
• Leverage SDLC toolchains to improve automation at scale.
• Contribute to engineering communities of practice and events.
• Work on cloud-native data, backend, and AI/ML initiatives at production scale.

Skills

Python

System design

Software engineering training

Enterprise development

SDLC knowledge

Microservices architecture

Cloud & DevOps

Cloud data engineering

ETL / AWS data stack

AI tooling governance

Responsible AI

Communication

Finance experience

AI/ML systems

Kubernetes / Docker

LLM / RAG / OpenSearch

Data science collaboration

Tools

Docker

Kubernetes

EKS

OpenSearch

Vector databases

Job description

Salary: £62,000 - 102,000 per year

Requirements:

• Formal training or certification in software engineering concepts with proficient applied experience
• Hands‑on practical experience in system design, application development, testing, and operational stability
• Proficiency in Python and other modern programming languages
• Experience developing, debugging, and maintaining code in a large corporate environment, including database querying languages
• Strong knowledge of the software development life cycle
• Proven track record in system design and in 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 such as ETL, Glue, S3, and Athena, as well as an MLOps stack
• Demonstrated experience leading the effective use of enterprise‑authorized AI‑assisted software development tools, with the ability to validate outputs for correctness, performance, and security
• Strong understanding of responsible AI use in engineering workflows, including data sensitivity, secure handling of inputs and outputs, and resiliency and security expectations
• Ability to communicate design choices and results clearly to stakeholders with diverse backgrounds
• Experience with data, AWS, and AI/ML engineering in commercial settings, preferably in financial services
• Experience working on recommendation systems, LLM applications, or other AI/ML systems
• Practical experience with Kubernetes, EKS, Docker, and MLOps
• Prior exposure to LLMs, RAG, knowledge graph technologies, OpenSearch, and vector databases
• Prior experience collaborating with data scientists

Responsibilities:

• Execute software solutions, design, development, and technical troubleshooting to build solutions and solve complex technical problems
• Create secure and high‑quality production code and maintain algorithms that run synchronously with appropriate systems
• Produce architecture and design artifacts for complex applications and ensure design constraints are met through software code development
• Build the engineering stack required for data and AI/ML products, including data engineering, backend engineering, cloud infrastructure DevOps, and MLOps
• Design and implement data engineering solutions using modern big data technologies
• Drive adoption and governance of approved AI‑assisted engineering practices to improve code quality, delivery speed, and operational outcomes
• Apply knowledge of SDLC toolchain capabilities, including approved AI‑assisted development and automation tools, to improve automation value at scale
• Contribute to software engineering communities of practice and events exploring new and emerging technologies
• Work on challenging cloud‑native data, backend engineering, and AI/ML engineering initiatives to industrialize AI/ML models at production scale

Technologies:

• AI
• AWS
• OpenSearch
• Big Data
• Backend
• Cloud
• DevOps
• Docker
• ETL
• Support
• Kubernetes
• LLM
• MLOps
• Python
• RAG
• Security
• microservices

More:

We are JPMorgan Chase, a global leader in financial services, and within our Commercial & Investment Bank Markets Research Technology team we are building trusted, market‑leading technology products in a secure, stable, and scalable way. We offer the opportunity to work in a highly technical, hands‑on senior engineering role on cloud‑native data, backend, and AI/ML solutions that support our business objectives. We value learning, problem‑solving, creative thinking, and a can‑do attitude, and we are committed to diversity, inclusion, and equal opportunity across our global workforce. Our Commercial & Investment Bank serves corporations, governments, and institutions in more than 100 countries, providing strategic advice, raising capital, managing risk, and extending liquidity around the world.