Director of AI

About the role

This is not a pure management role. Initially, roughly 75% of the role will be hands-on technical work and 25% will be team leadership and management. You will be expected to make key technical decisions yourself, build critical systems, and help recruit and lead a small team of senior generative AI engineers.

Responsibilities

• Own the company’s AI/ML technology and feature direction across the product
• Define and execute the technical AI roadmap, balancing near-term product delivery with longer-term platform investment, technical debt reduction, and strategic innovation
• Deliver technical, product, and operational outcomes tightly aligned with company goals and overall business success
• Hire, mentor, and manage a small team of senior generative AI engineers (Expected team size: 2–5)
• Partner closely with Product Management and Project Management to balance new feature delivery against execution of the technical roadmap
• Lead architecture and implementation for core AI systems including:
  • LLM-based workflows
  • RAG systems
  • AI agents
  • Evaluation and testing systems
  • Observability and performance monitoring
  • Model selection and routing
  • Data ingestion and retrieval systems
• Own major parts of the company’s data ingestion pipeline into platform storage and analytics systems, including ETL-related design and execution where it supports AI product capabilities
• Work across graph databases, traditional databases, retrieval systems, and analytics infrastructure to support product quality and scale
• Own the AI vendor and external service provider budget, with responsibility for evaluating cost, performance, and strategic fit
• Evaluate proprietary and open-source model options, and select the right models for the right tasks
• Build infrastructure to host LLMs in the company’s new data center environment using company-provided hardware
• Establish strong experimentation and measurement practices for AI features, including A/B testing, offline evaluations, and production-informed assessment loops
• Serve as an internal evangelist for effective use of AI agents inside the engineering organization, especially for coding workflows
• Maintain and continuously improve a practical set of coding agents and AI-assisted engineering practices that help the team produce better software

Requirements

• 15+ years of experience in software engineering, machine learning, AI, or closely related technical fields
• Meaningful prior engineering management experience
• Proven track record building and shipping production AI/ML systems
• Strong hands-on depth with modern AI systems, especially in areas such as:
  • LLMs
  • generative AI applications
  • RAG
  • agents
  • model evaluation
  • observability
  • data pipelines / ETL
  • vector, graph, and relational data systems
• Experience selecting, integrating, and operating external AI vendors and services with cost accountability
• Experience evaluating and deploying open-source models in production or near-production environments
• Strong system design judgment and the ability to move fluidly between architecture, implementation, and operational execution
• Comfort operating in an early-stage, pre-revenue startup where speed, ownership, and technical judgment matter
• Ability to lead senior engineers while remaining deeply involved in design and execution