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Python- AI Software Engineer III

JPMorgan Chase
Wilmington, USA
Full-time
Mid · 3+ years experience
Onsite
Discovered 2 weeks ago
awsdatabricksecsekskafkakubernetes

Full Job Posting

Job responsibilities

  • Execute software solutions, design, development, and technical troubleshooting with the ability to think beyond routine or conventional approaches to build solutions or break down complex technical problems
  • Create secure and high-quality production code and maintain algorithms that run synchronously with appropriate systems, with a focus on Python backend development and PySpark-based data processing
  • Build, deploy, and support scalable data engineering modules on Databricks, ensuring reliable performance, maintainability, and alignment with platform architecture standards
  • Leverage enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity across complex deliverables (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards; contribute learnings and reusable patterns to improve broader team effectiveness
  • Apply knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation
  • Produce architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development
  • Gather, analyze, synthesize, and develop visualizations and reporting from large, diverse financial data sets in service of continuous improvement of software applications and systems
  • Proactively identify hidden problems and patterns in data and use these insights to drive improvements to coding hygiene and system architecture
  • Participate in code reviews, providing and incorporating constructive feedback to continuously elevate code quality and engineering standards across the team
  • Collaborate with product managers, architects, and cross-functional engineering teams to translate finance business requirements into scalable technical solutions

Required qualifications, capabilities, and skills

  • Formal training or certification on software engineering concepts and 3+ years applied experience
  • Hands-on practical experience in system design, application development, testing, and operational stability
  • Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages
  • Proficiency in Python backend development with hands-on experience building and optimizing PySpark data pipelines in production environments
  • Demonstrated experience with Databricks, including module development, deployment, and ongoing operational support
  • Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, test creation, troubleshooting, or documentation) with demonstrated ability to critically evaluate, validate, and refine AI-generated outputs for correctness, performance, and security
  • Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage within team practices
  • Solid understanding of databases (Snowflake, Databricks, SQL, DB2 or NOSQL)

Preferred qualifications, capabilities, and skills

  • Experience with Apache Spark, Kafka, or similar distributed data processing frameworks in a large-scale enterprise environment
  • Exposure to cloud-native development and AWS services, particularly AWS EMR, Glue, ECS, EKS (Elastic Kubernetes Service) for deploying and managing containerized applications
  • Exposure to AI/ML data platforms

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