Director, AI Strategy & Mental Health

Job Description

Job Description

Description

The Jed Foundation (“JED”) is a nonprofit organization that protects emotional health and prevents suicide for teens and young adults. By equipping individuals, families, schools, and communities with the skills, knowledge, and support to promote mental well-being, JED is committed to ensuring that all young people have the resources they need to thrive. Position Overview The Jed Foundation (JED) is seeking a AI Safety & Wellbeing to advance JED’s growing work at the intersection of artificial intelligence, emerging technology, mental health, and suicide prevention. AI is rapidly changing how people learn, connect, create, seek information and support, form relationships, and navigate the world around them. JED’s work in this area spans advising technology companies; AI safety, evaluation, and benchmarking collaborations; partnerships with research and public-interest organizations; public thought leadership and guidance; and efforts to understand and shape both the risks and potential benefits of emerging technologies. Reporting to the SVP, Youth Strategies & Chief Engagement Officer, the Director will advance key areas of work focused on emerging AI technologies and their implications for mental health and suicide prevention, AI safety and evaluation, technology advising, and the development of JED positions, frameworks, and guidance. The successful candidate will bring meaningful existing expertise in AI technology and safety or evaluation, along with experience applying technology, safety, research, or evaluation approaches in mental health, healthcare, public health, child and adolescent wellbeing or safety, or another high-stakes human context. The role requires understanding of mental health and suicide prevention to work effectively with JED’s experts and partners, alongside the technical fluency to engage credibly with AI researchers, safety and evaluation teams, engineers, and product leaders.

• Maintain a sophisticated understanding of developments in AI technology and assess their implications for mental health and suicide prevention, including emerging forms of human-AI interaction such as conversational and relational AI, multimodal systems, agents, memory and personalization, ambient and wearable technologies, and embodied AI. 
• Advance JED’s work in AI safety, evaluation, benchmarking, standards, and related field-building efforts, working with technology, research, mental-health, suicide-prevention, and public-interest partners to bring relevant priorities into evaluation frameworks, scenarios, constructs, measures, and other approaches. 
• Apply knowledge of model and system behavior, safety evaluations, red-teaming, safeguards and mitigations, failure modes, and evaluation methodology to identify where current approaches are strong and where important gaps remain. 
• Advance approaches that consider not only acute safety failures but broader questions involving relationships and dependency, connection and belonging, agency, coping, help-seeking, protective factors, developmental differences, and beneficial uses of AI. 
• Manage substantive technology-company advising work, assessing AI products, features, and safety approaches and developing actionable recommendations related to model and product behavior, safety, evaluation, developmental appropriateness, help-seeking and crisis pathways, relational dynamics, and responsible deployment. 
• Develop JED POVs, frameworks, principles, recommendations, and guidance on AI and emerging technology, drawing on technical and research developments, expert consultation, JED expertise, and learning across external engagements. 
• Identify emerging issues, evidence gaps, and opportunities that warrant JED engagement through advising, guidance, partnerships, evaluation, field-building, or other strategic action. 
• Build and manage substantive relationships across technology companies, AI safety and evaluation organizations, academic and independent research institutions, public-interest organizations, philanthropy, and mental-health and suicide-prevention organizations. 
• Collaborate with JED’s Knowledge & Advising, Policy, Programs, MarComms, and other teams to bring relevant expertise into the work and connect insights from AI partnerships and advising to JED’s broader efforts. 
• Represent JED in appropriate collaborations, working groups, expert processes, convenings, and external forums, and contribute to the development of new initiatives, partnerships, proposals, and funding opportunities. 

Required  

• Approximately 7+ years of relevant professional experience, including substantial work in AI, AI safety, responsible AI, AI evaluation, human-AI interaction, or a closely related field. Exceptional candidates with a different career trajectory but equivalent depth of experience will be considered. 
• Strong working knowledge of contemporary AI technologies, including generative AI, large language models, multimodal systems, conversational AI, agents, memory/personalization, and emerging human-AI interfaces. 
• Demonstrated knowledge of AI safety and evaluation, including model and system behavior, evaluation and benchmarking, red-teaming, failure modes, safeguards and mitigations, and the strengths and limitations of current approaches. 
• Experience applying technology, safety, evaluation, research, or related expertise in a high-stakes human domain such as mental health, suicide prevention, healthcare, public health, child and adolescent wellbeing or safety, child protection, online safety, violence prevention, or another closely related area. 
• Working knowledge of mental health, suicide prevention, behavioral health, public health, or an adjacent field sufficient to engage meaningfully with domain experts and understand the implications of AI systems for people experiencing distress or vulnerability. 
• Technical fluency sufficient to engage credibly and independently with AI researchers, engineers, evaluation and safety teams, and product teams. This role does not require the candidate to be an ML engineer. 
• Demonstrated ability to connect technical developments to their implications for human behavior, safety, wellbeing, products, institutions, or society. 
• Excellent analytical, synthesis, writing, and communication skills, with experience developing frameworks, strategy, recommendations, guidance, or thought leadership. 
• Strong judgment and comfort working across technical and nontechnical disciplines in an area where technology, evidence, practice, and regulation are evolving rapidly. 
• Experience advancing complex work involving multiple internal and external stakeholders, with strong relationship-building and collaboration skills. 

Strongly Preferred  

• Direct experience in mental health, suicide prevention, behavioral health, digital mental health, or a closely related field. 
• Experience focused on children, adolescents, families, development, or populations experiencing heightened vulnerability. 
• Experience working directly with technology-company product, safety, evaluation, or research teams. 
• Experience developing or applying benchmarks, evaluations, safety frameworks, standards, or red-teaming approaches. 
• Experience translating technical research for public-interest, product, policy, practitioner, or other nontechnical audiences. 

An advanced degree in computer science, HCI, information science, behavioral or social science, public health, or another relevant discipline may be valuable but is not required.