Think of Us

Product Manager

• Define and maintain the ConnectMe product roadmap within Think of Us’ organizational strategy and program goals.
• Decide what gets built, in what order, why it matters, and what the team will not pursue.
• Frame work in terms of user, staff, service-quality, and operational outcomes.
• Prioritize feature opportunities, user feedback, operational needs, defects, technical debt, research findings, and state requests.
• Make tradeoffs among speed, scope, quality, learning, safety, and long-term sustainability visible.
• Present the roadmap to leadership, program teams, technology teams, and state partners.
• Evaluate and shape emerging product opportunities, documenting problems, hypotheses, outcomes, success criteria, constraints, risks, and expected learning.
• Work with Design and Engineering on research, feasibility, architecture, security, privacy, maintenance, and technical debt.
• Own acceptance criteria and product release decisions.
• Define AI boundaries, human-review requirements, failure conditions, quality expectations, evaluation frameworks, monitoring, and limitations.
• Decide whether AI capabilities are ready to release, should be limited, require iteration, or should be paused.
• Define success measures and use analytics, qualitative research, field observations, operational evidence, and AI evaluations to iterate.
• Coordinate with program leadership, state partners, Community Responders, young people, families, and caregivers.
• Distinguish product solutions from operational, practice, training, policy, or other interventions.
• Lead the cross-functional product team through priorities, decisions, and shared outcomes.
• Own release planning, dependencies, pilots, phased releases, deployments, monitoring, support, and rollback plans.
• Coordinate Product, Design, Engineering, Data and AI, Program, and Implementation.
• Establish lightweight product practices, standards, roadmap communication, release readiness, measurement, and decision documentation.
• Use AI tools to accelerate research synthesis, prototyping, analysis, documentation, testing, and coordination while maintaining human judgment and data safeguards.

Product Lead

Artificial Intelligence

• Define and drive Think of Us’s data strategy and roadmap, anchored on the Lived Experience Engine.
• Direct the architecture of the Databricks data lake, including tiering, data model evolution, and standards.
• Set standards for data quality, governance, and platform reliability.
• Translate organizational priorities into data investments and team structure.
• Build evaluation frameworks using LangFuse and custom tools for AI pipelines and agents.
• Own decisions regarding RAG architecture, agent grounding, retrieval quality, and future ML capabilities.
• Define the boundary between the data team and Applied AI Engineering for evaluations and AI data infrastructure.
• Build and maintain data governance and HIPAA-adjacent compliance standards.
• Own data access controls, privacy policies, and the ethical framework for lived-experience data.
• Ensure sensitive PII handling meets legal and ethical standards.
• Directly manage the data team and grow it over time.
• Build the processes, culture, and norms of the data function.
• Work hands-on as an individual contributor for the first 6–12 months.
• Provide architectural feedback on Databricks gold-layer models.
• Design evaluation frameworks for the ConnectMe AI pipeline and define quality standards for human-vetted output.
• Translate research questions into data roadmap priorities with program leadership.
• Review AI pipeline outputs for accuracy and equity across demographic groups.
• Assess evaluations and determine what is ready to ship, needs iteration, or should be briefed to Product.
• Draft data access policies for lived-experience narratives.
• Partner with executive leadership, Engineering, Product, Design, Program, and Policy leaders on technical direction and data-informed decisions.

Product Lead

Director of Data, AI