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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Director, Software Engineering & SaaS Platforms - **Company:** UL Solutions Inc. - **Location:** United States - **Salary:** $177,000.0 - $236,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Computing Platforms, Software as a Service, Continuous Integration, DevOps, Machine Learning, Software Architecture, Secure Coding, Software Engineering, Information Technology, Data Analytics, Data Management - **Published:** August 3, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=08fc1091ab135114 ## About the Role * Bachelor's degree in computer science, Engineering, or a related field (Master's preferred). * Extensive experience in software engineering, with multiple years in senior engineering leadership roles. * Proven success leading large-scale software platforms or SaaS products. * Strong understanding of modern software architectures, cloud platforms, DevOps practices, and secure development. * Demonstrated ability to lead through change and scale organizations. Preferred Experience * Experience leading AI-enabled, data-driven, or platform-centric software products. * Global or matrixed organizational leadership. * Budget ownership and investment prioritization. * Background in regulated or enterprise environments. Success Measures * Delivery predictability and product quality * Platform scalability and reliability * Engineering talent retention and growth * Alignment between engineering output and business outcomes ## Description The Director of Software Engineering provides strategic and operational leadership for software engineering teams responsible for designing, building, and scaling high quality software platforms and products. The role bridges business strategy and technical execution, ensuring engineering outcomes deliver customer value, operational excellence, and long term platform scalability. This leader sets technical direction, develops engineering talent, and partners closely with Product, Platform Engineering, Security, Data, and Business leaders to drive innovation and reliable delivery across portfolios. 1. Engineering & Technical Leadership * Define and drive the software engineering strategy and technical roadmap aligned with the Product Roadmap, business priorities and product vision. * Ensure adoption of engineering best practices across architecture, development, testing, CI/CD, security, and reliability. * Guide platform scalability, performance, and resilience across cloud and SaaS environments. * Evaluate and introduce new technologies where they create measurable business value (e.g., AI/ML, data platforms, automation). 2. Delivery & Execution * Own end-to-end delivery accountability for software initiatives, ensuring predictable execution, quality, and speed to market. * Partner with Product Management to translate business and customer needs into executable engineering plans. * Use AI to assist with product development and deployment of AI capabilities in our customer-facing solutions. * Establish and monitor KPIs and engineering metrics related to delivery, quality, reliability, and team health. * Ensure compliance with security, privacy, and regulatory standards across software products. 3. People & Organizational Leadership * Build, lead, and develop high-performing engineering managers and teams. * Set clear accountabilities, performance objectives, and growth paths for leaders and individual contributors. * Foster a culture of technical excellence, ownership, inclusion, and continuous improvement. * Support workforce planning, succession, and capability development aligned to future needs. 4. Cross-Functional & Stakeholder Partnership * Collaborate with Product, Architecture, Security, Data, Operations, and Business leaders (GMs) to align priorities and execution. * Communicate complex technical topics clearly to executive and non-technical stakeholders.Represent Software Engineering in strategic planning, investment decisions, and governance forums Success Measures * Delivery predictability and product quality * Platform scalability and reliability * Engineering talent retention and growth * Alignment between engineering output and business outcomes ## Related Videos - [From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform](https://www.wearedevelopers.com/videos/100018-from-devops-to-scaled-devops-how-we-re-rebuilding-continuous-delivery-as-a-platform) - [How to Cause (or Prevent) a Massive Data Breach- Secure Coding and IDOR](https://www.wearedevelopers.com/videos/39-how-to-cause-or-prevent-a-massive-data-breach-secure-coding-and-idor) - [PySpark - Combining Machine Learning & Big Data](https://www.wearedevelopers.com/videos/44-pyspark-combining-machine-learning-big-data) - [User 1st! Technology 2nd! Stop building AI nobody uses - start delivering real business outcomes](https://www.wearedevelopers.com/videos/100337-user-1st-technology-2nd-stop-building-ai-nobody-uses-start-delivering-real-business-outcomes) - [Platform Engineering vs. DevOps Why not both?](https://www.wearedevelopers.com/videos/885-platform-engineering-vs-devops-why-not-both) - [DevOps Maturity Check – a way to balance autonomy and alignment](https://www.wearedevelopers.com/videos/58-devops-maturity-check-a-way-to-balance-autonomy-and-alignment) ## Related Articles - [What is Software Engineering?](https://www.wearedevelopers.com/magazine/289-what-is-software-engineering) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Stephan Gillich - Bringing AI Everywhere](https://www.wearedevelopers.com/magazine/489-stephan-gillich-bringing-ai-everywhere) - [Now is the time for industrialized software development](https://www.wearedevelopers.com/magazine/601-now-is-the-time-for-industrialized-software-development) - [What is Software Engineering in the Age of AI?](https://www.wearedevelopers.com/magazine/640-what-is-software-engineering-in-the-age-of-ai)