Chief Technology Officer

CaterTrax•Rochester, NY

4d•Hybrid

About The Position

The Chief Technical Officer (CTO) is a C-suite executive and a member of the senior leadership team, accountable for defining and executing CaterTrax®'s enterprise technology vision in direct support of the company's AI business transformation strategy. As the company's most senior technologist, the CTO holds full executive ownership of the technology function and its contribution to enterprise growth, value creation, and constituent indispensability. Reporting directly to the CEO and partnering with the Board and executive leadership team, the CTO serves as the company's ultimate technology authority, with end-to-end ownership of the entire technology organization — spanning enterprise and AI architecture, data engineering, platform and software engineering, and information security. The CTO is a strategic leader who bridges business objectives with technical execution — setting technical direction, championing modern engineering practices, accelerating AI integration across product and operations, and ensuring the security and scalability of the current and future-state CaterTrax® platform. The CTO leads primarily through the technology organization's directors and managers, retaining the technical depth to guide architecture and hold the quality line. The role ensures that technology decisions compound platform excellence and support our constituent model before creating technical debt or fragmentation. This includes all internal and external users and systems. The company is hybrid but qualified remote applicants are encouraged to apply.

Requirements

15+ years of progressive technology leadership experience, including at least 5 years in a C-level or equivalent most-senior-technologist role (CTO, CIO, or SVP/EVP of Engineering) with full ownership of a multi-functional technology organization.
Demonstrated experience leading teams of engineers and technical professionals in a B2B SaaS or technology product environment.
Proven track record of building and scaling cloud-native platforms (AWS, Azure, or GCP) in production environments.
Hands-on experience designing or overseeing AI/ML implementations, including LLM integration, predictive modeling, or data pipeline architecture.
Deep expertise in modern software engineering practices: microservices, APIs, CI/CD, containerization (Docker/Kubernetes), and Agile delivery methodologies.
Experience owning data architecture and data governance in a product or enterprise context.
Demonstrated ability to lead information security programs and maintain compliance with relevant industry frameworks (SOC 2, PCI-DSS, etc.).
Strategic thinking: Translates ambiguous business challenges into clear, executable technology strategy.
Executive presence: Communicates complex technical concepts to non-technical audiences including Board, customers, and investors.
Talent development: Builds, motivates, and retains high-performing, diverse engineering teams.
Bias for action: Moves decisively with incomplete information; comfortable operating in a dynamic, growth-stage environment.
Collaborative influence: Builds alignment and momentum across Engineering, Product, Sales, and Customer Success.
Financial acumen: Manages technology budgets, vendor contracts, and build-vs-buy decisions with sound business judgment.
Deep proficiency is expected in at least one discipline per category.
Large language model (LLM) platforms: OpenAI / Azure OpenAI, Anthropic Claude, AWS Bedrock, or equivalent.
AI/ML frameworks and tooling or Python-based AI stacks.
Retrieval-augmented generation (RAG) architecture design and vector database platforms.
AI ops tooling for model monitoring, versioning, drift detection, and deployment pipelines.
Cloud platforms: deep proficiency in Microsoft Azure, with architectural fluency across all AWS and Google.
Containerization and orchestration: Docker and Kubernetes (EKS, AKS, or GKE).
Serverless and event-driven architecture patterns
Cloud data warehouse and lakehouse platforms.
Data pipeline and transformation tooling.
Power BI
SQL, Relational and Vector databases.
Source control and collaboration: Git, GitHub, or GitLab — including branching strategies, PR workflows, and code review practices.
CI/CD pipeline platforms: GitHub, Azure DevOps
API design and management
Agile and project management tooling: Jira, Confluence (Atlassian suite experience preferred).
Security information and event management.
Identity and access management (IAM): Okta, Azure Active Directory, SSO/SAML/OAuth 2.0 protocols.
Vulnerability scanning and dependency management.
Compliance automation platforms (SOC 2, PCI-DSS).
Microsoft 365 suite: Teams, SharePoint, Excel, and PowerPoint at a power-user level for executive reporting and communication.
Design collaboration: Figma or equivalent for cross-functional work with Product and UX teams.
AI productivity tools: Microsoft Copilot, Anthropic Claude, or similar for personal and team enablement.

Nice To Haves

Master's degree (MBA, MS Computer Science, or equivalent) preferred.
Experience in foodservice technology, hospitality tech, or enterprise SaaS platforms serving multi-site operators.
Familiarity with AI governance frameworks and responsible AI deployment at scale.
Experience serving as the most senior technologist through a comparable AI or platform transformation at a company of similar size and scope.
Track record of successful technology M&A integration or platform consolidation.

Responsibilities

Define and communicate the multi-year technology roadmap aligned to business transformation and growth objectives.
Partner with the CEO and executive leadership team to translate business strategy into actionable technology initiatives and investment priorities.
Serve as a member of the executive leadership team and report regularly to the Portfolio on technology strategy, roadmap progress, risk posture, and investment priorities.
Serve as the organization's primary technology spokesperson with the customers, partners, and portfolio (as needed).
Build and sustain a high-performing, collaborative culture grounded in accountability, innovation, and continuous learning.
Lead organizational planning including headcount, team structure, skills development, and succession across all technical disciplines.
Own the enterprise AI architecture strategy, including the selection of AI/ML frameworks, platforms, and tooling to enable scalable, production-grade AI features.
Drive the development and governance of core data model, ensuring data integrity, accessibility, and readiness to support AI and analytics workloads.
Champion the integration of AI capabilities — including generative AI, predictive analytics, and automation — into the product suite and internal operations.
Establish AI governance policies covering model explainability, bias detection, data privacy, and responsible use in alignment with applicable regulations.
Collaborate with Product and Customer Success to identify and prioritize high-impact AI use cases across the client lifecycle.
Provide executive oversight of platform engineering and infrastructure, ensuring the platform is scalable, reliable, observable, and cost-efficient.
Guide software engineering teams in architectural decision-making, engineering standards, and the adoption of DevOps/DevSecOps practices and CI/CD pipelines.
Oversee the full software development lifecycle (SDLC), quality assurance processes, and release management practices.
Drive platform modernization efforts, including cloud strategy, API design, microservices evolution, and technical debt reduction.
Champion engineering velocity and quality through the adoption of relevant tooling, metrics and Agile/Lean practices.
Maintain executive accountability for information security posture, policies, and compliance obligations (SOC 2, PCI-DSS, GDPR, or applicable standards).
Oversee security architecture, vulnerability management, incident response, and third-party risk management programs.
Ensure security is embedded throughout the SDLC and platform operations.
Partner with Legal and Compliance to proactively address evolving regulatory requirements and data protection obligations.
Directly lead the technology leadership team, including the platform and engineering directors, providing coaching, succession planning, and performance management.
Drive employee engagement, career pathing, and recognition practices across the technology organization.
Establish clear goals, OKRs, and accountability frameworks for all technical teams.