Director of AI Architect, Headspace Health

• 10+ years of software engineering experience, with at least 4 years focused on the design and delivery of production AI/ML systems at scale
• Deep expertise in modern AI architectures, including LLMs, RAG systems, embedding pipelines, agentic frameworks, and real-time inference, with hands-on experience moving these from prototype to production
• Proven ability to define AI strategy at an organizational level: translating ambiguous business challenges into technical roadmaps, influencing executive stakeholders, and driving alignment across cross-functional teams
• Strong command of responsible AI principles: safety, fairness, explainability, data privacy, and the unique ethical considerations of AI in health and wellness contexts
• Extensive experience with cloud-native AI infrastructure (AWS, GCP, or Azure), containerized deployment (Kubernetes), and MLOps practices including model serving, monitoring, and evaluation pipelines
• Demonstrated ability to evaluate and integrate third-party AI providers, orchestration frameworks (e.g., LangChain, LlamaIndex, or similar), and vector/embedding database systems
• Exceptional communication skills: you can articulate complex AI trade-offs clearly to both technical engineers and non-technical executives, and write specs that bring entire organizations along with you
• Ownership mindset: you are comfortable navigating ambiguity, making consequential architectural decisions with incomplete information, and taking accountability for outcomes across teams

Desirable

• 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
• 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, evaluation, and integration of AI/ML infrastructure, including model providers, vector databases, orchestration frameworks, and MLOps tooling, balancing build vs. buy decisions with long-term strategic implications
• Collaborate with Data Science, ML Engineering, and Product teams to ensure AI systems are grounded in high-quality, privacy-preserving data pipelines and continuously improve through rigorous feedback loops
• Establish AI engineering standards and best practices across squads, from prompt engineering and context management to model versioning, observability, and production monitoring
• Mentor and elevate engineers, ML practitioners, and technical leads across the organization, helping teams build confidence and competency in applied AI development
• Serve as Headspace's internal and external thought leader on AI, representing the company's technical vision in recruiting, partnerships, and the broader industry
• Identify and evaluate emerging AI capabilities (reasoning models, multimodal systems, fine-tuning approaches) for near-term applicability to Headspace's roadmap