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Lead Software Engineer - Payments Processing

JPMorganChase
Full-time
On-site
Tampa, Florida, United States
Description

Be an integral part of an agile team that's constantly pushing the envelope to enhance, build, and deliver top-notch technology products.

As a Lead Software Engineer at JPMorgan Chase within the Payments Processing group, you will play a pivotal role within the Commercial and Investment Bank's Payments Technology group. You will be an integral part of an agile team dedicated to enhancing, building, and delivering trusted, market-leading technology products in a secure, stable, and scalable manner. As a core technical contributor, you will be responsible for executing critical technology solutions across multiple technical domains, supporting the firm’s strategic business objectives.

Job responsibilities

  • Execute creative software solutions, encompassing design, development, and technical troubleshooting. Leverage your ability to think beyond conventional approaches to build innovative solutions and deconstruct complex technical problems
  • Regularly provides technical guidance and direction to support the business and its technical teams, contractors, and vendors
  • Develop secure, high-quality production code, and conduct thorough reviews and debugging of code written by peers to ensure adherence to best practices and security standards
  • Drives decisions that influence the product design, application functionality, and technical operations and processes
  • Serves as a function-wide subject matter expert in one or more areas of focus
  • Actively contributes to the engineering community as an advocate of firmwide frameworks, tools, and practices of the Software  Development Life Cycle
  • Influences peers and project decision-makers to consider the use and application of leading-edge technologies
  • Adds to the team culture of diversity, equity, inclusion, and respect
  • Lead evaluation sessions with external vendors, startups, and internal teams. Drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for integration within existing systems and information architecture
  • Identify opportunities to eliminate or automate the remediation of recurring issues, thereby enhancing the overall operational stability of software applications and systems

 

Required qualifications, capabilities, and skills

 

  • Formal training or certification in software engineering concepts, with 5+ years of applied experience in software development
  • Hands-on practical experience delivering system design, application development, testing, and operational stability
  • Advanced skills in one or more programming languages, particularly Python, with a strong emphasis on writing clean, efficient, and maintainable code
  • Advanced knowledge of software applications and technical processes with considerable in-depth knowledge in one or more technical disciplines (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)
  • Ability to tackle design and functionality problems independently with little to no oversight
  • Experience with cloud-native solutions and platforms, particularly AWS, and proficiency in infrastructure as code using Terraform
  • Experience in Computer Science, Computer Engineering, Mathematics, or a related technical field
  • Familiarity with big data technologies such as Apache Spark and in-memory data grids like GemFire
Preferred qualifications, capabilities, and skills
 
  • Proficiency in automation and continuous delivery methods, ensuring seamless integration and deployment processes
  • Strong understanding of telemetry and observability patterns to monitor and improve system performance and reliability
  • Comprehensive understanding of all aspects of the Software Development Life Cycle, with a focus on agile methodologies such as CI/CD, application resiliency, and security
  • Demonstrated proficiency in software applications and technical processes within a specialized technical discipline (e.g., cloud computing, artificial intelligence, machine learning, mobile technologies)