Director, AI Architect
$230,000–$287,500 year
Hybrid · San Francisco, California, United States
Job Summary
Director, AI Architect at Headspace responsible for defining and leading the AI architecture strategy and end-to-end AI systems across streaming content, conversational AI, coaching, therapy, and psychiatry services. Owns technical vision, establishes reusable platform components, guides responsible AI practices, evaluates and integrates AI providers and infrastructure, and mentors engineering teams while collaborating with executives to translate business opportunities into concrete roadmaps. The role emphasizes production-grade AI at scale, privacy-preserving data pipelines, governance, and leadership in an AI-first transformation in a regulated mental-health tech context.
Required Qualifications
- 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
- 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
- BS/MS/PhD in Computer Science, Machine Learning, or a related field, or equivalent practical experience
- Experience in digital health, wellness, or a similarly regulated consumer domain, with familiarity with HIPAA, data minimization practices, and the heightened standard of care for AI in sensitive user contexts
- Background in fine-tuning, RLHF, or domain-adapted model training for specialized consumer applications
- Experience with conversational AI, dialogue systems, or AI-powered coaching/companionship products
- Familiarity with Server-Driven UI (SDUI) and how AI-driven personalization integrates with dynamic, schema-based rendering across web and mobile clients
- Track record of building AI evaluation frameworks — including automated evals, red-teaming, and human-in-the-loop review pipelines
- Experience driving AI governance initiatives, including model cards, audit trails, and cross-functional risk review processes
Apply with one swipe on Sorce. We auto-fill applications and apply on your behalf — no cover letters, no 40-minute forms.
Hiring someone like this?
Get your role in front of qualified candidates on Sorce.