JPMorgan Software Engineer III Python 

United States, New York 

312512335

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
• Creates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systems
• Assesses the vision of the business or key stakeholders and advises on technology options, risks, and costs versus benefits of various approaches
• Researches where solutions to business needs currently exist within or outside the technology platform, and if not, whether new solutions are amenable to the technology available
• Understands business processes, products and operations to design, develop and implement solutions fit for requirement
• Provides third line production support
• Adds to team culture of diversity, equity, inclusion, and respect

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 3+ years of applied experience
• Hands-on practical experience in system design, application development, testing, and operational stability
• Proficient in coding in one or more languages
• Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages
• Overall knowledge of the Software Development Life Cycle
• Solid understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
• Demonstrated knowledge of software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)

Preferred qualifications, capabilities, and skills

• Hands on experience in Python programming (experience in production systems using Python)
• Bitbucket/Git, version control
• SQL skills (Able to work with data easily in a hands-on manner)
• Prior experience with cloud deployments of machine learning tech stacks (training and inference utilizing AWS SageMaker or equivalent) and/or Large Language Models is strongly preferred