Senior Engineering Manager - Brain Health

Responsibilities

• Build next-generation therapeutic AI agents that deliver personalized pain reprocessing and mindfulness interventions, ensuring clinical efficacy while maintaining engaging, empathetic user experiences.
• Architect and scale a unified education platform that intelligently serves pain science content, tracks learning progress, and personalizes pathways to build member confidence in movement.
• Develop the technical strategy for brain health initiatives, ensuring alignment between technological capabilities and therapeutic best practices in partnership with product and clinical stakeholders.
• Design robust AI architectures for conversational therapy bots that maintain context over multiple sessions and adapt therapeutic approaches based on member progress.
• Establish MLOps practices specific to mental health AI, including model monitoring for therapeutic effectiveness, safety guardrails, and compliance with healthcare standards.
• Drive innovation in NLP and affective computing to enhance the therapeutic alliance between AI agents and members.
• Build cross-functional partnerships with content creators, clinical psychologists, and data scientists to create a comprehensive brain health ecosystem.

Basic Qualifications

• Bachelor's degree in Computer Science, Engineering, or related field
• 5+ years of experience managing teams of 5+ technologists (mix of engineers and ML researchers/scientists)
• 5+ years of experience building and deploying ML/NLP solutions at scale (thousands to millions of DAU)
• Experience with conversational AI, dialogue systems, or chatbot development

Preferred Qualifications

• Master’s degree or higher in Machine Learning, Computational Psychology, or a related field
• 3+ years of experience developing conversational or agentic AI systems using LLMs (e.g., GPT, Claude, LLaMA), including techniques such as prompt engineering, RAG, fine-tuning, or reinforcement learning
• Proven understanding of responsible AI and ethical model design, particularly within healthcare or sensitive data environments
• Experience building or deploying digital mental health or therapeutic AI applications, with familiarity in CBT, DBT, or other evidence-based modalities
• Working knowledge of mental health privacy regulations (HIPAA, state-specific laws) and secure data practices
• Proficiency in modern development and ML infrastructure (Python, TypeScript, Node.js/NestJS, vector databases, LangChain, Docker, Kubernetes, AWS services like Bedrock/SageMaker, and CI/CD pipelines)