JPMorgan Lead Software Engineer 

United Kingdom, Scotland 

631159261

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
• Creates secure and high-quality production code, and reviews and debugs code written by others. Maintains algorithms that run synchronously with appropriate systems
• Embraces AI/RAG based technologies, not only for the generation of software, but through the creation of our capabilities that depend upon it.
• Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development
• Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture
• Adds to team culture of diversity, equity, inclusion and respect

Required Qualifications, Capabilities and Skills

• Formal training or certification on software engineering concepts and proficient advanced experience
• Hands-on practical experience in system design, application development, testing, and operational stability, including modelling, scaling, and object oriented concepts
• Proficient in coding in one or more languages including Java and possibly Python.
• Experience in the use of GPT, LLM, RAG, Gen AI, Prompt Engineering related technologies
• Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages.
• Current experience of agile methodologies such as CI/CD, Applicant Resiliency, and Security
• Exposure to cloud technologies (AWS or GCP) via hands on experience or certification
• Solid understanding of software applications and technical processes within a related technical discipline (e.g. data ingestion, data storage, data serving, APIs, etc.).
• Hands-on experience in data lake or data warehouse and related technologies (e.g. Spark, ETL, Databricks).