Co-founder & Chief Technology Officer - AI ROI Measurement Platform

The opportunity

Enterprises spent ~$644B on AI in 2025, yet 72% of initiatives are destroying value, and 69% of leaders have lost visibility into which AI tools their teams use. Each vendor reports usage differently — logins, tokens, API calls — and finance teams cannot consolidate. CFOs and CIOs cannot answer the one question their boards are asking: Did we get ROI?

The answer is a vendor-neutral measurement and governance platform that captures AI activity wherever it happens, benchmarks utilization, proficiency, and business impact, and gives the CFO and CIO an auditable view of value creation across the enterprise. Think Nielsen for enterprise AI, with an autonomous FinOps layer on top.

The category window is roughly 18 months before horizontal incumbents extend in. The teams that ship a credible, vertically-anchored, outcome-priced platform inside that window will define it. We intend to be one of them.

The partnership

The CEO co-founder is in place. The customer thesis is validated, design partners are engaged, and the market work is complete. What remains is to bring on the technical co-founder.

This is a co-founder role, not a CTO hire. The distinction matters.

You will write the first lines of production code. You will set the architecture, the data model, the engineering culture, and the security posture. You will represent the company in front of CIOs, Chief AI Officers, CFOs, security teams, and investors. You will recruit and lead the founding engineering and applied AI team. In return, you receive founder-level equity, founder-level authority, and a genuine partnership with the CEO on every material decision.

What you will build in the first 18 months

• Months 0–3. Ship the discovery layer with a design partner — browser extension and endpoint agent capturing AI usage across ChatGPT, Claude, Gemini, Copilot, and the long tail without per-vendor integrations. Establish the core architecture and 15-minute refresh pipeline.
• Months 3–6. Deliver the Utilization × Proficiency × Value framework, including the first GitHub/Jira correlation for engineering ROI. Convert three paid pilots. Begin SOC 2 Type II readiness with zero-content-retention as a non-negotiable design constraint.
• Months 6–9. Release GA v1 covering discovery, analytics, proficiency benchmarking, and governance controls aligned to EU AI Act, ISO 42001, and NIST AI RMF. Convert pilots to ten paying enterprise customers. Finalize pricing — including outcome-based pricing on captured savings.
• Months 9–18. Ship the governed AI access hub and expand into a vertical specialization — most likely an autonomous AI FinOps agent for a regulated industry — that no horizontal incumbent can credibly follow. Reach $1M ARR. Build out the founding team.

Requirements:
You will thrive in this role if

• You have shipped data-intensive, multi-tenant SaaS into enterprise production, with buyers including CIOs, CFOs, and CISOs.
• You hold the full stack confidently: browser extensions and endpoint agents, high-throughput event ingestion, real-time analytics pipelines, applied LLMs and prompt-quality evaluation, and the demands of secure multi-tenant SaaS (SOC 2, tenant isolation, audit logging, data residency).
• You have well-formed convictions about telemetry design, privacy-preserving instrumentation, and the line between observation and surveillance — developed through production experience, not from reading about it.
• You favour systems that perform consistently across heterogeneous enterprise environments over systems that demonstrate well in controlled settings.
• You are prepared to operate as a principal — setting the technical agenda, making decisive calls in uncertain conditions, and owning the outcomes.

Strongly preferred

• Prior founder, or early-stage technical leadership experience.
• Background in enterprise observability, FinOps, security analytics, or governance/GRC platforms — categories where the buyer expects auditable evidence, not narrative.
• Direct experience shipping browser extensions or endpoint agents at enterprise scale.
• Applied LLM evaluation experience: prompt-quality scoring, output benchmarking, or model-routing systems, including the cost, quality, and privacy trade-offs of self-hosting foundation models.

Benefits:
What we are offering

• Founder-level equity. A meaningful ownership stake, structured for long-term value creation and aligned across funding rounds.
• Founder-level authority. Co-decision rights on product, technology, hiring, fundraising, and strategy. A board or board-observer seat, as appropriate to the cap table and stage.
• A committed partner, FutureSight co-founding team.
• Pre-seed capital. FutureSight invests directly in the venture at pre-seed