We have an exciting opportunity for a Lead Software Engineer at UL Research Institutes, within our Digital Safety Research Institute (DSRI). This is a REMOTE opportunity 

The Lead Software Engineer is a major contributor to the development and maintenance of complex software systems of Digital Safety. The Lead Software Engineer provides technical guidance, mentorship, and leadership to the team while collaborating with stakeholders to deliver high-quality software solutions. 

UL Research Institutes: 

At UL Research Institutes (ULRI), we expand the boundaries of safety science to create a more secure and sustainable world. For more than a century, we have studied the unintended consequences of innovation, designed solutions to mitigate risk and shared our findings with academia, scientists, manufacturers, and policymakers across industries. We identify critical safety and sustainability issues, asking tough questions because we believe a safer world begins with knowledge. 

Digital Safety Research Institute: 

The Digital Safety Research Institute (DSRI) addresses unresolved safety risks and emerging dangers in the world’s digital ecosystem. We aim to help protect people from unwanted access to personal devices and privacy, algorithms, and disinformation threats by working to create a new digital safety ecosystem. 

DSRI is committed to sharing digital safety insights, collaborating with key stakeholders, and offering extensive outreach and education to help support safer digital environments for people everywhere. 

What you’ll learn and achieve: 

As the Lead Software Engineer, you will play a key role in the rapid growth of UL as you: 

• Lead, define, and develop full-stack software systems and platforms that enable large-scale research, evaluation, and dissemination of safety insights 

• Implement service boundaries, data model evolution, integration patterns between our platforms, and the pipelines and evaluation frameworks they feed 

• Set technical direction across projects, aligning architecture and data frameworks with DSRI’s evolving research priorities and the broader AI evaluation ecosystem 

• Iterative design of complex, ambiguous, cross-cutting systems where the problem isn’t fully understood 

• Ensure consistency in engineering practices and set the standard for AI-assisted engineering on the team, including the use of Claude Code on large refactors, greenfield work, and adopted code from external organizations; developing patterns and documentation to accelerate software engineering. 

• Provide feedback to teams using AI coding tools in a dangerous, inappropriate, or inefficient way. 

• Provide guidance and informal mentorship to junior engineers to support skill development and knowledge sharing. 

• Foster a collaborative and positive work environment, promote knowledge sharing and professional growth within the team. 

• Assist in hiring, onboarding, and training new software engineers, ensuring a smooth integration into the team. 

• Represent technical work across the organization and in select external settings 

• Contribute to and/or lead other department specific and cross-functional initiatives. 

What makes you a great fit: 

While no one candidate will embody every quality, the successful candidate will bring many of the following professional competencies and personal attributes: 

• 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 

Professional education and experience requirements for the role include: 

• Bachelor’s degree in computer science, or equivalent combination of education and experience. Master’s degree preferred. 

• Minimum 8 years of experience in software development, with a focus on platform security and proficiency in multiple programming languages and frameworks. 

• Experience deploying several complex software products and understands the nuances of the software development life cycle. 

About UL Research Institutes and UL Standards & Engagement