CTO

Channel Fusion is accelerating its AI-enabled platform strategy and technical organization during a critical growth window. We are seeking a full-time Chief Technology Officer to lead AI strategy, technical modernization, and architecture direction: establishing a rigorous, real-time operating system and measurement framework for engineering that provides visibility into output, quality, and business impact, and building a comprehensive technical foundation that demonstrates platform scalability, architectural maturity, and operational excellence. This is a full-time, hands-on operating role — not an advisory role.

The CTO owns technology strategy, architecture standards, AI-enabled engineering transformation, cybersecurity and platform-risk direction, technology investment priorities, and enterprise technical readiness. The Head of Engineering reports to the CTO and owns the engineering organization, engineering people leadership, and day-to-day software delivery. The VP, Cloud Security & Client Delivery also reports to the CTO and owns cloud and security operations, compliance execution, service reliability, and client-delivery execution. The CTO aligns these functions and resolves cross-functional technology, roadmap, security, client, and investment tradeoffs with the CEO and executive leadership team.

Core Mandate

• Technical Readiness & Operating Baseline — Build a comprehensive technical foundation that demonstrates platform scalability, architectural maturity, and operational excellence to internal stakeholders and enterprise partners. This includes: stored-procedure inventory, technical debt registry (with owner, business impact, remediation plan for every material item), modernization status evidence (production validation, monitoring, rollback testing, legacy deprecation), and infrastructure/scalability metrics (concurrent users, transactions per minute, multi-tenant support, cost per 1,000 transactions).
• Client Onboarding Scalability — Establish clear metrics and targets for client onboarding efficiency, documentation, and platform-driven configuration to enable faster, more predictable client launches, and build the roadmap to onboard new clients at scale without linear growth in engineering headcount.
• AI Strategy & Productivity — Establish an engineering baseline and launch a controlled AI-assisted delivery pilot within the first 30 days using a live codebase and real delivery workflows. Within the first 90 days, demonstrate measurable improvement in cycle time or throughput without deterioration in quality, security, or production reliability. Define a validated rollout plan for the remaining pods based on pilot results, including projected engineering and AI-tooling economics.
• Architecture Direction — The CTO will initially serve as Channel Fusion's senior architecture authority and assess the technical-leadership model during the first 30 days. The CTO may recommend principal-level architecture capacity where demonstrated workload, technical risk, or delivery leverage justifies it. Any such position will be structured as a hands-on technical role within the engineering organization rather than as an additional management layer.
• Operating Framework — Establish a real-time management system that provides visibility into organizational output: a weekly pod-level scorecard (mission, committed vs. delivered outcomes, revenue/retention supported, team size, work mix, cycle time, quality, loaded cost, and capacity, investment, ownership, and operating recommendations for each pod), and a technology economics model (fully loaded org cost, cost by pod, revenue/retention by pod, AI tooling/token costs, RPE tracking against target, and modeled efficiency, investment, capacity, and operating-leverage scenarios).
• Executive & Board Engagement — Report progress against a monthly operating and readiness dashboard directly to the CEO/ELT; translate technical reality into terms leadership and enterprise partners can act on.

Key Qualifications

• 15+ years of technology leadership experience within enterprise software, SaaS, MarTech, or channel marketing platforms; prior experience as CTO, SVP, or VP of Engineering/Technology at meaningful scale.
• Bachelor's degree in a relevant field or equivalent demonstrated experience required; advanced technical or business education preferred.
• Personally designed and led the implementation of an AI-assisted software delivery system in a live engineering organization — not simply sponsored, approved, or directed one from a distance. Able to speak specifically to the tools, workflow design, failure modes encountered, and measurable before-and-after results (cycle time, defect rates, throughput, or cost).
• Track record modernizing legacy platforms while continuing to ship to live, paying clients — real modernization under real constraints, not a greenfield build or an unconstrained migration.
• Experience leading distributed engineering organizations, including India-based teams — familiar with the timezone, communication, and career-development dynamics required to build genuine technical ownership and trust across geography.
• Able to connect technical investment decisions to business outcomes — client onboarding speed, release velocity, operational resilience, and enterprise value — not just architectural or code-quality terms.
• Deep working knowledge of modern AI technologies: LLMs, tokenization, prompt engineering, RAG, vector databases, GPU/cloud AI infrastructure, and AI software stacks, sufficient to personally design and lead an AI-native engineering organization.
• Experience directing enterprise-grade, cloud-native, secure, multi-tenant SaaS architecture at the senior-most technical level.
• Technical diligence experience — has built or defended a technical readiness package (debt inventory, architecture risk, scalability evidence) for board, executive, enterprise-partner, or other senior stakeholder review.
• Excellent executive communication skills; able to lead a multi-functional technical organization (engineering, cloud/security, and client delivery) as a unified executive team.
• Genuine investment in building organizational bench strength over time, including mentoring and developing technical leaders as part of a collaborative, growth-oriented leadership approach.
• MarTech / Through-Channel Marketing Automation (TCMA) experience — desirable, not required.

What Success Looks Like — First 90 Days

• A complete, evidence-based Technology Operating Pack in active use (pod scorecard, AI productivity proof, tech economics, engineering operations charter, technical readiness baseline).
• Clear, quantified metrics and targets for client onboarding efficiency and platform-driven configuration, with a documented roadmap to scale.
• A monthly operating and readiness dashboard populated with real baselines and trending in the right direction on debt reduction, modernization, and scalability.
• At least one priority engineering pod has used the new AI-assisted delivery system to ship a meaningful client-visible or operationally important production outcome, with documented before-and-after evidence covering cycle time, quality, cost, and required manual effort.
• A validated resilience and disaster-recovery baseline is complete, including recovery-time and recovery-point requirements, backup and restoration evidence, material infrastructure risks, and a prioritized remediation plan.
• Clear decision rights, operating boundaries, escalation paths, and shared performance metrics are established across the CTO, Head of Engineering, and VP, Cloud Security & Client Delivery — including the interfaces among engineering delivery, cloud operations, security and compliance, client commitments, and architecture governance.