Headspace

Healthcare

Director,AIArchitect

$250–350k ~AI est. San Francisco, California, United States FULL TIME Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Director candidates.

The Brief

“Director, AI Architect at Headspace”

Industry & Context.

Healthcare
Full Job Description

About the Director, AI Architect at Headspace: At Headspace, our mission is to transform mental healthcare from an episodic need to an everyday care practice by offering an AI-powered, clinically safe, and personalized Mental Health Companion. AI is central to how we fulfill that mission at scale. As our Director, AI Architect, you will own the technical vision and execution of Headspace's AI-first service transformation, designing the systems, patterns, and practices that embed intelligence across every layer of our product and platform. Reporting directly to the Chief Product & Engineering Officer, you will operate at the intersection of applied research, ML science, and platform engineering. This is a rare opportunity to shape how a category-defining mental health company thinks about, builds with, and deploys AI, responsibly, scalably, and in ways that genuinely improve member outcomes. What you will do: Define and lead Headspace's overarching AI architecture strategy, establishing the foundational patterns, platforms, and principles for an AI-first service transformation across our portfolio of streaming content, conversational AI, coaching, therapy and psychiatry services. Architect end-to-end AI systems: including LLM-powered features, agentic workflows, retrieval-augmented generation (RAG), and real-time personalization, with a relentless focus on reliability, safety, and member impact. Partner directly with the executive team, product leadership, and senior engineering stakeholders to align AI strategy with company goals, translating business opportunities into concrete technical roadmaps. Author company-wide technical specs that establish AI design principles, evaluation frameworks, guardrails, and reusable platform components. Drive responsible AI practices across the organization, including model evaluation, bias mitigation, explainability, data governance, and compliance with evolving regulatory standards relevant to health tech. Lead the selection, eva

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