About The Position
Enterprises are spending billions on AI, yet a significant portion of initiatives are destroying value, and many leaders lack visibility into AI tool usage. Current vendor reporting methods are inconsistent, making it impossible for finance teams to consolidate data and for CFOs and CIOs to determine ROI. This role is for a vendor-neutral measurement and governance platform that captures AI activity, benchmarks utilization and impact, and provides an auditable view of value creation. The goal is to define the enterprise AI measurement category within an 18-month window. The CEO co-founder is in place, the customer thesis is validated, and design partners are engaged. This is a co-founder role, not a hire, requiring the individual to write the first lines of production code, set the architecture, data model, engineering culture, and security posture. The role involves representing the company to key stakeholders, recruiting and leading the founding engineering and applied AI team, and receiving founder-level equity, authority, and a genuine partnership with the CEO.
Requirements
- Shipped data-intensive, multi-tenant SaaS into enterprise production, with buyers including CIOs, CFOs, and CISOs.
- Full stack confidence: 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).
- Well-formed convictions about telemetry design, privacy-preserving instrumentation, and the line between observation and surveillance, developed through production experience.
- Preference for systems that perform consistently across heterogeneous enterprise environments.
- Prepared to operate as a principal — setting the technical agenda, making decisive calls in uncertain conditions, and owning the outcomes.
Nice To Haves
- Prior founder, or early-stage technical leadership experience.
- Background in enterprise observability, FinOps, security analytics, or governance/GRC platforms.
- 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.
Responsibilities
- Write the first lines of production code.
- Set the architecture, data model, engineering culture, and security posture.
- Represent the company in front of CIOs, Chief AI Officers, CFOs, security teams, and investors.
- Recruit and lead the founding engineering and applied AI team.
- Ship the discovery layer with a design partner, including a browser extension and endpoint agent capturing AI usage.
- Establish the core architecture and a 15-minute refresh pipeline.
- Deliver the Utilization × Proficiency × Value framework, including GitHub/Jira correlation for engineering ROI.
- Begin SOC 2 Type II readiness with zero-content-retention as a design constraint.
- Release GA v1 covering discovery, analytics, proficiency benchmarking, and governance controls aligned to EU AI Act, ISO 42001, and NIST AI RMF.
- Ship the governed AI access hub and expand into a vertical specialization, such as an autonomous AI FinOps agent for a regulated industry.
- Build out the founding team.
Benefits
- Founder-level equity.
- Founder-level authority.
- Co-decision rights on product, technology, hiring, fundraising, and strategy.
- A committed partner, FutureSight co-founding team.
- Pre-seed capital.
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What This Job Offers
Job Type
Full-time
Career Level
founder
Education Level
No Education Listed
