
11 - 50 employees
🤖 Artificial Intelligence
🤝 B2B
Venture Capital • Artificial Intelligence • B2B
FutureSight is a venture studio that co-founds and funds B2B AI ventures, building scalable world-class businesses with values-driven leaders. Based in Toronto, New York, and San Francisco, FutureSight collaborates with entrepreneurs by providing a supportive community of experienced product leaders, business designers, engineers, marketers, and growth hackers. This 'Dream Team' aids in refining ideas from inception to scale, developing co-founders into transformational leaders. FutureSight focuses on various sectors, including health tech, education tech, and fintech, offering a rigorous process for validating ideas and investing in great talent and concepts.
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11 - 50 employees
🤖 Artificial Intelligence
🤝 B2B
Venture Capital • Artificial Intelligence • B2B
FutureSight is a venture studio that co-founds and funds B2B AI ventures, building scalable world-class businesses with values-driven leaders. Based in Toronto, New York, and San Francisco, FutureSight collaborates with entrepreneurs by providing a supportive community of experienced product leaders, business designers, engineers, marketers, and growth hackers. This 'Dream Team' aids in refining ideas from inception to scale, developing co-founders into transformational leaders. FutureSight focuses on various sectors, including health tech, education tech, and fintech, offering a rigorous process for validating ideas and investing in great talent and concepts.
• Write the first lines of production code, set the technical direction, and lead execution end-to-end • Establish the core architecture, engineering culture, and security posture, including SOC 2 readiness, tenant isolation, encryption, and audit logging • Ship a marketing review prototype into production with a design partner early adopter, then deliver communications surveillance, trading oversight, audit-ready logs and reporting; release GA v1 covering all core modules except regulatory filings within 9 months, and expand into regulatory filings and enterprise integrations through 18 months • Own the training and constant evolution of the core AI/LLM model, delivering robust and highly reliable analysis • Own the explainability layer that produces audit-ready evidence on demand, and the reliability engineering that ensures the platform performs consistently in the field • Represent the company in front of all customer constituencies and third-party interests, as well as investors, as the technical voice of the venture • Convert pilots into ten paying customers and reach $1M ARR within 18 months, partnering with the CEO on conversion and fundraising • Recruit and lead the founding engineering and applied AI team, and establish the cultural foundation of the company
• Shipped LLM-powered systems into production environments where incorrect outputs carried real consequences — not prototypes or demonstrations • Full-stack confidence across applied LLMs, RAG, retrieval, deterministic rules engines, human-in-the-loop workflows, observability, and secure multi-tenant SaaS (SOC 2, tenant isolation, encryption, audit logging) • Well-formed convictions about explainability and reliability engineering, developed through direct production experience • Preference for systems that perform consistently in the field over systems that demonstrate well in controlled settings • Prepared to operate as a principal — setting the technical agenda, making decisive calls under uncertainty, and owning the outcomes that follow • Strongly preferred: prior founder, founding engineer, or early-stage technical leadership experience; background in legal tech, RegTech, fintech compliance, healthcare, or another high-trust regulated vertical; familiarity with the U.S. wealth management ecosystem, including SEC and FINRA workflows, marketing review, communications surveillance, and trade monitoring; direct experience self-hosting or privately deploying foundation models
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