Head of Engineering

Head of Engineering Ninety.io | Remote (US: Pacific to Eastern)  Why Ninety Ninety is the leading EOS® software trusted by 18,000+ companies to help business owners run stronger businesses and grow valuations. We bring vision, goals, execution rhythm, and business metrics into one connected platform, backed by an ecosystem of expert support, professional services, partners, and AI.  We have strong financials with a long runway, we lead our category, and we’re investing in product marketing as a growth engine. If you enjoy building, shaping strategy, and tying your work to measurable outcomes, you’ll have real ownership here. Why this role, why now Ninety is at an inflection point: the product is evolving quickly, and the business is ready to level up how we take new capabilities to market. We’re opening a new Head of Engineering role for someone who can build repeatable systems and raise the bar for what “great” software engineering looks like in a lean, high-impact environment. What you’ll own Define and execute the engineering strategy aligned to company objectives, product roadmap, and long-term platform scalability Lead the evolution of the company’s technology organization as it adapts to an increasingly AI-enabled product and operational future Build and scale a high-performing engineering organization  Establish strong engineering operating principles grounded in agile development, iterative delivery, rapid feedback loops, and continuous improvement Drive execution excellence across planning, prioritization, delivery predictability, operational reliability, and technical quality Collaborate deeply with Product, Design, Stakeholders, and Executive Leadership to translate ambiguous business opportunities into executable strategies Create a culture that balances speed, innovation, customer impact, and long-term technical sustainability Own architecture evolution and technical decision-making, ensuring systems remain scalable, secure, resilient, and adaptable Lead adoption of AI technologies across both the product portfolio and internal engineering workflows where they create measurable leverage Develop engineering managers and technical leaders capable of scaling with the organization Establish metrics, processes, and organizational mechanisms that improve visibility, accountability, and execution consistency Ensure engineering practices support enterprise-grade security, compliance, reliability, and customer trust expectations Drive recruiting and organizational design strategies to attract and retain exceptional engineering talent Foster strong cross-functional collaboration while helping the organization operate effectively through rapid change and ambiguity What Success Looks Like: Engineering consistently delivers high-quality product capabilities with increasing speed, predictability, and customer impact The engineering organization scales effectively without excessive process overhead or loss of agility AI capabilities become a meaningful differentiator in both product experience and internal operational efficiency Teams demonstrate strong ownership, accountability, autonomy, and cross-functional collaboration Engineering leaders and ICs operate effectively in ambiguous environments and can independently drive clarity and execution Agile principles are deeply embedded in day-to-day operations, including iterative/incremental delivery, continuous learning, retrospectives, and rapid adaptation Technical debt is proactively managed while enabling continued product velocity Platform reliability, scalability, security, and operational maturity improve alongside company growth Hiring, onboarding, and talent development processes produce a strong and sustainable engineering culture Engineering becomes a trusted strategic partner to Product, Design, Customer Success, and executive leadership Organizational planning and prioritization improve alignment between business goals and engineering investment Teams embrace experimentation, data-informed decision making, and continuous improvement Customers experience improved product quality, performance, innovation velocity, and reliability What we’re looking for Proven experience leading and scaling engineering organizations within high-growth SaaS environments, ideally through Series B/C stages Demonstrated ability to lead organizations through periods of rapid growth, ambiguity, and organizational evolution Strong technical background with the ability to engage deeply in architecture, systems design, platform strategy, and engineering tradeoff discussions Experience incorporating AI/ML capabilities into products, platforms, workflows, or engineering operations Deep understanding of modern software development practices, cloud-native architectures, DevOps, CI/CD, observability, and platform reliability Strong commitment to agile development principles, iterative/incremental execution, continuous delivery, and customer-centered product development Demonstrated success building high-performing engineering cultures that emphasize ownership, accountability, collaboration, and learning Experience hiring, mentoring, and developing engineering managers and senior technical leaders Ability to create structure and drive execution in environments where requirements and priorities may evolve rapidly Strong communication and executive alignment skills, including the ability to translate complex technical topics into business outcomes Experience balancing short-term execution needs with long-term architectural and organizational health Strong product and business orientation with a focus on measurable customer and company impact Experience establishing engineering processes, metrics, and operational mechanisms appropriate for scaling organizations High degree of adaptability, pragmatism, and comfort operating in fast-moving environments with incomplete information Bachelor’s degree in Computer Science, Engineering, or related field preferred; equivalent practical experience welcomed This won’t be a fit if you prefer Highly structured environments with fully defined requirements, stable priorities, and long planning horizons before execution begins Separating engineering from product, business, or customer outcomes rather than operating as a deeply cross-functional partner Optimizing primarily for process, hierarchy, or organizational control over speed, adaptability, and pragmatic execution Maintaining legacy approaches without actively exploring how AI can transform products, engineering workflows, and organizational leverage Narrowly managing existing teams instead of building, evolving, and scaling organizations through ambiguity and change Perfection-driven delivery models that delay customer feedback rather than embracing iterative development, experimentation, and continuous improvement