Director, AI Platform & Enablement

Bullish•New York, NY

8d•$275,000 - $340,000

About The Position

Bullish is hiring a leader to own enterprise AI strategy and delivery across Bullish Group. The role will drive employee adoption, partner with business leaders to improve workflows, and lead the development of shared AI capabilities. It will work with Platform Engineering on supporting infrastructure and be accountable for delivery and measurable business results. As the first hire in this function, the successful candidate will work hands-on while building the team. The role combines technical leadership in AI architecture, business judgment in setting priorities, and communication with executives, engineers, and business teams. The posting also describes Bullish as an institutionally focused global digital asset platform providing market infrastructure and information services, including Bullish Exchange and CoinDesk products. Its engineering organization emphasizes security, compliance, technical excellence, and end-to-end ownership of outcomes.

Requirements

10+ years of experience in technical roles, including leadership of engineering or platform teams and a track record of delivering operational change.
Experience building and developing technical teams, including hiring, setting direction, and managing delivery.
Deep, current knowledge of AI models, agent systems, MCP, and RAG, backed by hands-on experimentation with emerging capabilities.
Ability to assess new AI approaches, identify practical applications, and guide adoption into production.
Hands-on experience building and deploying production AI systems, including agent workflows, tool integrations, evaluation, and guardrails.
Familiarity with tools such as LangChain, LangGraph, and Claude or OpenAI APIs.
Experience designing and operating secure, scalable AI platforms, including custom connectors, agent deployment pipelines, and shared infrastructure.
Ability to lead architecture decisions and assess engineering trade-offs.
Track record of working directly with business leaders and teams to identify problems, redesign workflows, drive AI adoption, and deliver measurable results.
In-house experience at a technology-focused organization, with responsibility for setting strategy, prioritizing investment, and delivering outcomes.
Clear communication and sound judgment, with the ability to influence senior executives, guide engineers, and help business teams put AI to use.

Nice To Haves

Experience in digital assets, financial services, or media.
Experience redesigning business processes or leading operational improvement programs.
Experience establishing a new function, including hiring the team, setting priorities, and putting operating practices in place.
Active participation in the AI community through technical writing, speaking, open-source contributions, or practitioner groups.

Responsibilities

Own enterprise AI strategy for Bullish Group, identify valuable opportunities across business functions, set priorities, and take responsibility for delivery.
Build and lead the AI Platform & Enablement team, partnering with recruiting to hire, develop, and retain team members.
Own the AI capability roadmap and lead development of shared services, including agents, connectors, a skills library, and discovery tools.
Partner with Platform Engineering on infrastructure, deployment, reliability, and provider management.
Lead enterprise AI tool rollout, access, administration, and adoption; coordinate vendor requirements with Platform Engineering and connector security reviews with Security.
Build practical training programs for employees at different needs and skill levels, including baseline training, low-code workshops, bespoke training, and internal hackathons.
Work directly with business teams to redesign workflows and deliver solutions, building forward-deployed engineering capacity as the function grows.
Establish ownership for deployed solutions, including maintenance, support, and continued improvement, and equip business teams to manage appropriate capabilities independently.
Set and track measures of adoption, efficiency, and return on investment, and adjust priorities and execution when results fall short.
Evaluate advances in AI to inform platform and tooling decisions, and report progress, results, and strategic priorities to the CTO and COO.