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JPMorgan Lead Software Engineer - Systems Languages 
United Kingdom, England 
693312163

26.06.2024

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
  • Be a creative thinker capable of identifying solutions analysing inefficiencies in languages and developing innovative, sustainable solutions to optimise software performance including AI/ML.
  • Role encompasses R&D as well as engaging with the engineering community to share knowledge and drive change
  • Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems
  • Leads evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture
  • 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

Required qualifications, capabilities, and skills

  • Formal training or certification on software engineering concepts and mid level applied experience
  • Hands-on practical experience delivering system design, application development, testing, and operational stability
  • Advanced in one or more programming language(s) especially in system languages
  • Knowledge of code execution (compiler, bytecode, cross compilers, language virtual machines) technologies
  • Advanced understanding of agile methodologies such as CI/CD, Applicant Resiliency, and Security
  • Demonstrated proficiency in software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)
  • Apply AI/ML optimization approaches engineers e.g., pruning, quantization, fine-tuning, and prompt engineering.
Preferred qualifications, capabilities, and skills
  • Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience; advanced degree preferred.