Lead Software Engineer - Python, Data, Cloud, AIML
Lead Software Engineer on JPMorgan Chase's Commercial & Investment Bank Markets Research Technology team in London, a hands-on role building cloud-native data, backend, and AIML engineering to industrialize AI/ML models at production scale. Core stack: Python, AWS data services (Glue, S3, Athena), containers, Kubernetes, and MLOps.
- Compensation
- Not disclosed
- Location
- London, United Kingdom
- Work setup
- Not specified
- Seniority
- Lead
- Employment
- Not specified
- Experience
- Not specified
- Category
- Software engineering
- Posted
Skills
Must have
- Formal training or certification on software engineering concepts with 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 developing, debugging, and maintaining code in a large corporate environment with modern programming and database querying languages
- Demonstrated experience leading use of AI-assisted software development tools with validation of AI outputs for correctness, performance, and security
- Strong understanding of responsible AI use in engineering workflows, including data sensitivity and secure handling of inputs/outputs
- 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 clearly and communicate to stakeholders of various backgrounds; overall knowledge of the SDLC
Nice to have
- Experience with data, AWS and AIML engineering in commercial settings, preferably in financial sector
- Experience working on 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
Full 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 the Commercial & Investment Bank's Markets Research Technology team, 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
- Drives adoption and governance of approved AI-assisted engineering practices across teams to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test acceleration, release readiness, incident/root-cause analysis), while establishing measurable validation standards (secure coding, peer review, automated testing) and promoting reuse of proven patterns and automation within the SDLC/TLM toolchain.
- Applies knowledge of tools within the Software Development Life Cycle toolchain, including approved AI-assisted development and automation capabilities, to improve the value realized by automation at scale.
- 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 on software engineering concepts 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