JPMorgan Lead Software Engineer - AI Research 

United Kingdom, England, London 

480359963

This is a hands-on technical leadership role, and you will work with AI Researchers across any number of fields including Explainability (XAI), Fairness, Optimization, Synthetic Data, Cryptography and Markets/Trading Research (and many more). Whilst working closely with the researchers, your core deliveries will centre around the technology required to make AIML innovations and research operate at scale within a top tier investment and retail banking businesses.
Job responsibilities

• Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
• Develops secure high-quality production code, and reviews and debugs code written by others
• Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems
• Leads communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies
• Adds to team culture of diversity, equity, inclusion, and respect
• Leverage and integrate the latest AI advances into the firm’s workflow in a scalable and secure manner
• Create robust pipelines for repeatable model delivery

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering* concepts and advanced applied experience
• Strong track record of developing high quality, production code in Python
• Exceptional Cloud Engineering skills (both public and private), and a proven track record of navigating a complex technical environment and delivering robust solutions within those constraints
• Hands-on practical experience delivering system design, application development, testing, and operational stability
• Proficiency in automation and continuous delivery methods
• Proficient in all aspects of the Software Development Life Cycle
• Advanced understanding of engineering methodologies such as CI/CD, Application Resiliency, and Security
• Up to date understand of Model Development Life cycle, and best practices for managing the fast-moving model provisioning environment

Preferred qualifications, capabilities, and skills

• Experience in AI an advantage, interest in AI a must!
• Experience with AWS and Kubernetes
• Interest / understanding of statistics and optimization techniques
• Experience of integrating new tools/libraries into frameworks
• Track record of Big Data specific infrastructure (eg Spark) to achieve scale

that support the firm’s commercial goals by harnessing artificial intelligence and machine learning technologies to develop new products, improve productivity, and enhance risk management effectively and responsibly