Sr Lead Software Engineer - Java & Databricks

JPMorgan Chase JPMorgan Chase · Banking · OH · Corporate Sector

Senior Lead Software Engineer role focused on developing intelligent agent-based systems and optimizing data pipelines on Databricks, leveraging Java and Python. The role involves designing, training, and deploying AI agents, mentoring team members, and collaborating with cross-functional teams in an enterprise environment with AWS cloud experience.

What you'd actually do

  1. Lead the design and implementation of robust, scalable Java applications, leveraging advanced features and frameworks to optimize performance and maintainability.
  2. Mentor team members in best practices for Java coding, testing, and debugging, ensuring high-quality code and adherence to industry standards.
  3. Develop intelligent agent-based systems that autonomously perform complex tasks, leveraging machine learning and advanced AI techniques.
  4. Collaborate with cross-functional teams to design, train, and deploy AI agents that enhance user experience and automate business processes.
  5. Build and optimize data pipelines on Databricks, utilizing Spark for large-scale data processing, analytics, and machine learning workflows.

Skills

Required

  • Java
  • Python
  • Databricks
  • Spark
  • AWS
  • software engineering concepts
  • system design
  • application development
  • testing
  • operational stability

Nice to have

  • AI agentic development

What the JD emphasized

  • 5+ years of applied experience in enterprise environments
  • 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, etc.)

Other signals

  • Develop intelligent agent-based systems that autonomously perform complex tasks, leveraging machine learning and advanced AI techniques.
  • Collaborate with cross-functional teams to design, train, and deploy AI agents that enhance user experience and automate business processes.
  • Build and optimize data pipelines on Databricks, utilizing Spark for large-scale data processing, analytics, and machine learning workflows.