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UL Research InstitutesPosted 1 month ago

Lead Software Engineer - Technical Track

$131,186–$180,381 year

RemoteUnited States

Full TimeSenior LevelSmall

Job Summary

Lead full-stack software systems and platforms enabling large-scale research, evaluation, and dissemination of safety insights. Define service boundaries, data model evolution, and integration patterns between platforms and pipelines. Set technical direction across projects, aligning architecture with evolving research priorities and the broader AI evaluation ecosystem. Ensure consistency in engineering practices, including the adoption of AI-assisted coding tools like Claude Code for refactors and greenfield work. Provide feedback on AI tool usage, mentor junior engineers, and assist in hiring and onboarding. Represent technical work across the organization and lead cross-functional initiatives. Requires deep expertise in React, Python, PostgreSQL, and containerized deployment, with 8+ years in platform security. Salary range $131,186.31-$180,381.17. Remote position within UL Research Institutes' Digital Safety Research Institute.

Required Qualifications

  • Bachelor's degree in computer science, or equivalent combination of education and experience
  • Minimum 8 years of experience in software development
  • Focus on platform security
  • Proficiency in multiple programming languages and frameworks
  • Experience deploying several complex software products
  • Understanding of the nuances of the software development life cycle

Desired Qualifications

  • Master's degree preferred
  • Deep expertise in software engineering, applied across the systems that support research and data-driven analysis (i.e., React in production at meaningful scale or complexity, Python services, async patterns, careful data handling, sensible API design, PostgreSQL, designing and implementing complex data structures, and working knowledge of the systems layer underneath, including containers, deployment, and observability)
  • Architectural judgment built on real experience (i.e., able to make choices from experience and articulate trade-offs, and able to know when not to introduce a new service, abstraction, or dependency)
  • Sophisticated use of AI coding tools, including integrating Claude Code or similar tools into substantial, non-trivial work and the ability to structure context, decompose problems, review generated code, and recover when the tools do not function properly
  • Track record of technical leadership without formal authority, with experience raising the level of teams through what you build and how you work
  • Clear, direct written communication and the ability to translate complex technical work for varied audiences (i.e., design documents, RFCs, post-mortems, asynchronous code reviews, and internal and external presentations)
  • Genuine interest in AI safety, test & evaluation, or one of specific harm domains (e.g., synthetic media, chatbot safety

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