Solo practitioners and small law firms still lose work the same way: missed calls, slow callbacks, and intake handled between hearings. Hiring is no answer — payroll, training, and turnover are exactly what these firms cannot absorb.
Problem and solution validation are complete. Multiple live pilots are entering production evaluation. The next phase is proving in-production reliability, delivery economics, and scalability. The teams that ship credible AI workers into trust-sensitive verticals in the next 18 months will define the category. We intend to be one of them.
The VentureBloomLex is a managed AI staffing platform that delivers AI workers as fully-set-up hires — trained, monitored, and continuously improved by our team. Rather than another self-serve SaaS tool, BloomLex operates as a Role-as-a-Service business: lawyers evaluate us on outcomes — time saved, calls answered, consults booked — not configuration effort.
Our first hire, Ava, is an AI Front Desk that answers calls 24/7, captures structured intake, books consultations, and performs outbound callbacks, without creating new operational burden for the lawyer. The roadmap expands from the front desk into adjacent AI staff roles, all delivered through the same managed model.
The PartnershipThe CEO co-founder is in place. The customer thesis is validated, design partners are engaged, and live pilots are running. What remains is to bring on the technical co-founder — a partner who will own product and engineering with the same conviction, urgency, and ownership stake.
This is a co-founder role, not a CTO hire. In return for that level of commitment, you receive founder-level equity, founder-level authority with co-decision rights on product, technology, hiring, fundraising, and strategy, and a genuine partnership with the CEO on every material decision.
What you'll ownAs Co-Founder & CTO, you will write the first lines of production code, set the technical direction, and lead execution end-to-end.
- Architecture & Reliability — Harden Ava's voice and workflow systems for in-production reliability. Establish core architecture, observability, and audit-trail standards
- RaaS Delivery Layer — Build the internal infrastructure that lets the team configure, monitor, and optimize AI performance without scaling engineering headcount
- Unit Economics — Own the trade-offs between AI quality and cost-per-call, and lock in unit economics within the $499/month pricing model
- Customer & Market — Represent the company in front of lawyers, partners, and investors as the technical voice of the venture
- Roadmap — Convert pilots into paying customers, expand the AI staff beyond the front desk, and begin a path toward custom and self-hosted models where legal and privacy requirements demand it
- Team — Recruit and lead the founding engineering team, and establish the cultural foundation of the company
- Shipped LLM-powered and voice systems into production environments where incorrect outputs carried real consequences
- Full-stack confidence across applied LLMs, real-time voice and conversational AI, telephony, human-in-the-loop workflows, observability, and secure multi-tenant SaaS
- Well-formed convictions about reliability engineering, edge-case management, and the trade-offs between AI quality and cost-per-call
- Experience building managed and service-heavy platforms, with the discipline to scale delivery without scaling engineering headcount
- Prepared to operate as a principal — including saying "this won't scale" or "this isn't ready" when the integrity of the product requires it
- Strongly preferred: prior founder or early-stage technical leadership experience; background in legal tech, healthcare, or another trust-sensitive vertical; capability to self-host custom models to meet legal and privacy needs
Please submit your resume, LinkedIn profile, and a brief note on why this venture aligns with your goals as a founder. We will move quickly for the right candidate.
FutureSight is committed to diversity, equity, and inclusion. We welcome applicants of all backgrounds and experiences.
Skills Required
- Shipped LLM-powered and voice systems into production where incorrect outputs carried real consequences
- Full‑stack experience with applied LLMs, real-time voice, conversational AI, telephony, human-in-the-loop workflows, observability, and secure multi-tenant SaaS
- Experience with reliability engineering, edge-case management, and trade-offs between AI quality and cost-per-call
- Experience building managed, service-heavy platforms and scaling delivery without proportionally scaling engineering headcount
- Ability to write production code, set technical direction, and establish architecture and observability standards
- Recruit and lead the founding engineering team and establish company engineering culture
- Represent the company as the technical voice to customers, partners, and investors
- Operate as a principal decision-maker, including making hard calls about readiness and scalability
- Prior founder or early-stage technical leadership experience
- Background in legal tech, healthcare, or other trust-sensitive verticals
- Capability to self-host custom models to meet legal and privacy requirements
What We Do
FutureSight is a venture studio that co-founds and funds vertical B2B AI software companies with values-driven entrepreneurs from zero to one, building world-class businesses.
