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

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.