Fractional CTO

The organization is spinning out an internally built sponsorship intelligence platform that automates reporting and provides predictive, AI-driven campaign insights. The team seeks a hands-on fractional CTO to professionalize the product’s technical foundation, strengthen security and compliance for enterprise prospects, and position the platform to scale as a standalone SaaS business. This role is mission-critical to convert enterprise opportunities, build technical credibility, and lay the groundwork for future engineering growth.

Responsibilities

• Rapidly assess the existing codebase and architecture; identify critical risks and produce a prioritized remediation plan
• Implement security and compliance controls required for enterprise evaluation (data protection, access controls, auditability)
• Harden deployment and operations: CI/CD, observability, incident response, backups, and recovery
• Validate and optimize data pipelines, partner integrations, and analytics workflows for reliability and accuracy
• Advise on and prototype predictive/AI features to ensure sound data science engineering practices and production readiness
• Join client and prospect technical conversations with BI, data, and analytics stakeholders to answer technical questions and build trust
• Define a technical product roadmap and short-term milestones that enable enterprise deals and scale
• Recommend team structure, hiring priorities, and tooling needed to transition from fractional leadership to a permanent engineering organization
• Provide hands-on code review, pair-programming, and technical mentorship during the engagement

Qualifications

• Proven experience as a hands-on CTO, fractional CTO, or senior engineering leader for early-stage SaaS or spinout products
• Strong software architecture and code review skills across web/backend, data pipelines, and analytics stacks
• Demonstrated experience implementing enterprise security and compliance controls (for example, SOC 2 readiness, data governance, and access controls)
• Practical knowledge of cloud infrastructure on major cloud providers, CI/CD, observability, and production operations
• Experience with data engineering, BI integrations, and deploying predictive/ML features into production
• Comfortable presenting to and collaborating with business, BI, and analytics stakeholders at enterprise customers
• Track record of defining technical roadmaps, scaling engineering teams, and hiring/prioritizing technical talent
• Flexible, part-time/fractional availability with the ability to start within a few weeks and adapt to evolving weekly commitments