VP of Engineering, Skylar AI

About ScienceLogic... ScienceLogic is redefining IT operations for the modern enterprise. Our AIOps platform empowers organizations to achieve Autonomic IT — where systems are self-healing, self-optimizing, and seamlessly aligned with business outcomes. We help enterprises and service providers gain unified visibility across hybrid and multi-cloud environments, automate workflows, and unlock performance at scale. We're accelerating digital transformation through the power of automation, AI, and analytics — giving IT and business leaders the tools to deliver superior customer experiences, drive efficiency, and innovate with confidence. We are seeking a visionary VP of Engineering to lead the development and delivery of ScienceLogic's Skylar AI platform. This is a rare opportunity to own and shape the engineering strategy for a transformative AI product from the ground up - building the teams, systems, and culture that will drive ScienceLogic's next decade of innovation. The ideal candidate is a deeply technical AI practitioner and proven engineering leader who thrives at the intersection of cutting-edge AI research and large-scale enterprise software delivery. You will report to the CPEO and work in close partnership with Product, Design, Sales, and Customer Success to build AI experiences that are not only technically exceptional but commercially impactful. Key Responsibilities Own the Skylar AI Engineering Vision • Working with the Skylar AI CTO, define and drive the end-to-end engineering strategy for the Skylar AI platform, including model architecture, inference infrastructure, data pipelines, APIs, and runtime services. • Translate product and business objectives into a compelling technical roadmap, with clear milestones, priorities, and measurable outcomes. • Serve as the primary engineering authority for Skylar AI—maintaining deep, hands-on engagement with core AI/ML systems, architecture decisions, and emerging capabilities. • Champion responsible and explainable AI practices, establishing engineering standards that ensure reliability, safety, fairness, and scale. Transform Engineering for an AI-First World • Lead the transformation of ScienceLogic's engineering processes, tooling, and culture to be AI-centric—embedding AI-assisted development, automated testing, and intelligent observability throughout the SDLC. • Champion modern engineering methodologies including AI-augmented CI/CD, LLM-assisted code review, and automated quality assurance pipelines. • Establish best practices for working with foundation models, fine-tuning workflows, RAG architectures, and AI evaluation frameworks. • Drive a culture of continuous experimentation and rapid iteration, enabling the team to quickly test hypotheses, learn from data, and ship with confidence. Build & Lead a World-Class Engineering Organization • Recruit, develop, and retain exceptional engineering talent, building diverse, high-performing teams capable of delivering category-defining AI products. • Create a culture of accountability, psychological safety, and excellence—where engineers are empowered to take ownership and push the boundaries of what's possible. • Define clear career paths, performance standards, and mentorship programs that attract top AI/ML engineers and grow them into future leaders. • Lead geographically distributed teams with consistency and clarity, fostering cohesion and alignment across time zones and functions. • Manage engineering capacity and resource planning to support aggressive growth targets while maintaining quality and sustainable team health. Drive Cross-Functional Alignment & Executive Partnership • Partner closely with the CTO, CPO, and executive leadership to align engineering investments with ScienceLogic's revenue growth and strategic priorities. • Collaborate with Sales, Marketing, and Customer Success to incorporate customer insights into the engineering roadmap and communicate platform capabilities with clarity and confidence. • Represent Skylar AI externally as a thought leader—speaking at industry events, engaging with key customers and partners, and elevating ScienceLogic's AI brand. • Communicate roadmaps, progress, risks, and tradeoffs with precision and transparency to all stakeholders, including the board of directors. Required Skills & Experience • 15+ years of progressive engineering leadership experience, including 5+ years in senior roles (VP or equivalent) leading large-scale product engineering organizations. • Deep, hands-on technical expertise in AI/ML—including experience with LLMs, neural networks, model training/fine-tuning, vector databases, RAG architectures, and AI evaluation methodologies. • Proven track record of transforming engineering organizations to adopt AI-centric development practices, tooling, and workflows. • Demonstrated success building and scaling high-performing, geographically distributed engineering teams in a fast-pa