Lead Software Engineer

Caterpillar Caterpillar · Industrial · Kosice, Slovakia

Lead Software Engineer at Caterpillar's digital and technology arm, focusing on building industry-leading digital solutions for customers and dealers using data, technology, advanced analytics, telematics, and AI capabilities. The role involves technical leadership, ensuring technical excellence, long-term maintainability, and healthy engineering practices within digital product areas. Responsibilities include managing the technical backlog, supervising test management, partnering with QA and support, setting code quality standards, and mentoring engineers, including responsible use of AI-assisted development tools.

What you'd actually do

  1. Own and continuously curate the technical backlog to reduce technical debt (including dependency upgrades, performance and reliability improvements, and security and compliance findings).
  2. Supervise test management and defect handling, ensuring bugs are clearly reported, categorized, and prioritized.
  3. Partner with QA and L2/L3 support to ensure production readiness and operation.
  4. Set clear expectations for code quality, test coverage, and delivery predictability, and continuously improve them using engineering metrics and datadriven insights.
  5. Enable and uplift engineers through mentorship, clearly defined standards, and modern development tooling, including responsible use of AIassisted development.

Skills

Required

  • HTML5
  • CSS3
  • React
  • Node.js
  • Next.js
  • JavaScript
  • TypeScript
  • REST API design and integration
  • SQL
  • distributed or microservicesbased systems
  • Authentication
  • authorization
  • entitlementdriven access models
  • AWS
  • Azure
  • CI/CD pipelines
  • Docker
  • cloudnative deployment patterns
  • automated testing
  • regression strategies
  • Testing frameworks
  • Playwright
  • Agile / Scrum environments
  • maintaining high engineering standards in production systems

Nice to have

  • Computer Science
  • Software Engineering
  • engineering excellence
  • maintainability
  • longterm system health
  • modernizing or stabilizing large, longlived codebases
  • production monitoring
  • observability
  • operational support

What the JD emphasized

  • responsible use of AIassisted development