Product Lead at Think of Us in Hybrid, Washington, DC

Job description

• Department: Technology & Innovation
• Reports to: Executive Leadership
• Direct Reports: N/A
• Location: Hybrid; Washington, DC (min. 3 days in the office)
• Category: Full Time/Exempt
• This is the first dedicated product-management role for the ConnectMe platform, taking over day-to-day product ownership from Executive Leadership.
• You will translate Think of Us’ organizational strategy, program goals, user needs, lived experience insights, and technical opportunities into a clear product strategy and roadmap. You will own decisions about what gets built, in what order, why it matters, and what the team will not pursue.
• Your primary focus will be ConnectMe, a reimagining of our resource navigation warmline that connects young people and families involved with the child welfare system to the resources and support they need. As Think of Us identifies additional product opportunities, you will also help evaluate and shape emerging ideas without allowing every promising concept to become an immediate roadmap commitment.
• We operate as a modern, AI-enabled product team. We define the outcomes we are trying to create, prototype and ship, measure performance in the real world, learn from users and operational evidence, and iterate.
• This is not government contracting or build-to-spec work. Our users include Think of Us staff and the children, young people, families, and caregivers they serve. State partners help us deploy and operate our services, while Think of Us retains responsibility for the core product direction and roadmap.
• The role requires the seniority to operate with significant autonomy in a lean, high-stakes environment, the technical fluency to make sound tradeoffs with engineers, and the judgment to recognize that not every organizational or operational problem should be solved through software..
• Think of Us’ CEO plays an active role in shaping the organization’s strategy and innovation agenda, identifying new opportunities, and setting the ambition and risk appetite for major product investments.
• The Product Lead is responsible for translating that strategic direction into a focused and executable product strategy. You will engage directly with ambitious and evolving executive ideas, clarify the underlying intent, test assumptions, and make clear recommendations about priority, scope, sequencing, tradeoffs, and risk.
• You are not expected to passively implement executive ideas, and an idea raised by an executive does not automatically become a roadmap commitment. You are expected to challenge assumptions constructively, make the implications for users, capacity, technical complexity, and existing priorities visible, and recommend the best path forward.
• Program leadership owns program outcomes, the service and practice model, safety, implementation, and field performance. The Product Lead owns product strategy, roadmap, prioritization, feature scope, product outcomes, and release decisions.
• The Lead Product & UX Designer owns research practice, interaction design, service experience, human-AI experience, and design quality. Engineering owns technical architecture, security, reliability, and implementation. Data and AI colleagues own the technical data platform, evaluation infrastructure, analysis, and AI quality evidence.
• The Product Lead brings these perspectives together into coherent product decisions.
• ConnectMe is a warmline and resource navigation platform where Community Responders work directly with help-seekers, including young people and families connected to the child welfare system.
• The platform is launching across multiple states. AI plays a growing role behind the scenes. It can draft an initial assessment and support plan for a responder to review and refine, suggest local resources matched to a family’s situation, and flag requests that may need urgent attention.
• In every case, AI should work in service of the people doing the work. It prepares, assists, and suggests, while people remain responsible for reviewing, correcting, deciding, and acting before information reaches a young person or family.
• Because this is sensitive work in a regulated and privacy-protected environment, product decisions must account for where AI creates value, where human judgment must remain central, how uncertainty is communicated, what safeguards are required, and how trust is earned.
• Over the coming year, the work will deepen. We will develop better tools for the staff who support families, learn more about how young people and caregivers want to share information and seek support in moments of stress, and make careful choices about how AI supports rather than replaces the human relationship at the center of the service.
• We recognize that candidates may not meet every listed qualification. Research shows that individuals from underrepresented groups are more likely to opt out of applying if they don’t meet 100% of the criteria. If you believe you meet many of the criteria and can succeed in this role, we encourage you to apply — we want to learn about your unique strengths and experiences.
• ConnectMe serves young people aging out of foster care, families navigating system involvement, caregivers trying to find help, and the staff supporting them. The Product Lead decides what the product team pursues and in what order. This person translates organizational strategy, program goals, lived experience, user needs, technical capacity, and evidence into a roadmap that makes the platform more useful, trustworthy, and effective.
• The right person brings clarity and care to consequential decisions. They know when to move quickly, when to gather more evidence, when to challenge an assumption, and when not to build. As Think of Us identifies additional product opportunities, this role will also help the organization distinguish between compelling ideas and products it is prepared to build, operate, evaluate, and sustain.

Responsibilities

• Own the Product Roadmap
• 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 outcomes, including the change in user experience, staff behavior, service quality, or operational performance the team is trying to create.
• Prioritize across 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 clearly to leadership, program teams, technology teams, and state partners.
• Revisit roadmap decisions when meaningful new evidence or organizational direction emerges.
• Evaluate Emerging Product Opportunities
• Write clear, well-scoped product and feature definitions that include the problem, hypothesis, intended outcome, success criteria, constraints, risks, and expected learning.
• Work with the Lead Product & UX Designer to ensure the experience is sufficiently researched and designed before development begins.
• Work with Engineering to understand feasibility, architecture, security, privacy, maintenance, and technical debt implications.
• Identify scope creep, hidden complexity, unclear requirements, and unresolved assumptions before they become delivery problems.
• Own acceptance criteria and product release decisions once required cross-functional reviews are complete.
• Document major decisions and the tradeoffs behind them.
• Shape AI Quality and Human-in-the-Loop Design
• Determine where AI genuinely helps and where human expertise, conventional software, operational changes, or no automation are more appropriate.
• Define what work AI may perform, what it may recommend, what requires human review, and what must remain human-led.
• Partner with Design, Engineering, Programs, the Director of Data & AI, and the Senior Applied Data Scientist on AI-enabled workflows.
• Define the intended user value, product boundaries, failure conditions, and quality expectations for AI features.
• Partner with the data and AI team on evaluation frameworks, datasets, quality thresholds, monitoring, and known limitations.
• Make product tradeoffs based on model performance, user experience, operational impact, equity, risk, cost, and reliability.
• Decide whether an AI capability is ready to release, should be limited, requires another iteration, or should be paused.
• Escalate direct-to-user AI, material safety concerns, or changes in organizational risk posture to executive leadership.
• Measure, Learn, and Iterate
• Define what success looks like for each major feature, including leading and lagging indicators and AI-specific quality measures where relevant.
• Partner with the Senior Director, Data Strategy and program leaders to connect product measures to broader program and organizational outcomes.
• Partner with Engineering and the data and AI team to ensure features are appropriately instrumented.
• Use product analytics, qualitative research, field observations, operational evidence, and AI evaluations to understand whether the product is working.
• Decide what to expand, revise, simplify, limit, or stop based on real-world evidence.
• Communicate clearly about what the evidence shows, what it does not show, and what the team still needs to learn.
• Build a culture of shipping, measuring, learning, and improving rather than building to a fixed specification.
• Work with Program and State Partners
• Coordinate with program leadership, state partners, Community Responders, young people, families, and caregivers to understand the problem space.
• Work with Programs to determine whether a need is best addressed through product, operations, practice changes, training, policy, or another intervention.
• Translate user needs, field signal, program requirements, and operational realities into product opportunities and decisions.
• Distinguish between state-specific requests and capabilities that should become part of the shared product.
• Evaluate customization requests based on strategic value, reuse, cost, and maintenance requirements.
• Communicate clearly about what is and is not on the roadmap and why.
• Avoid making commitments before product, technical, program, and capacity implications have been assessed.
• Establish structured feedback mechanisms that do not rely only on the loudest or most available stakeholders.
• Drive Releases and Coordinate the Team
• Lead the cross-functional product team through clear priorities, decisions, and shared outcomes.
• Own release planning, including what ships in each cycle, in what sequence, and with what dependencies.
• Coordinate across Product, Design, Engineering, Data and AI, Program, and Implementation.
• Ensure design, technical quality, security, data, program, implementation, and support readiness are considered before release.
• Identify risks and dependencies early.
• Coordinate quality assurance and launch readiness without personally owning every testing or implementation task.
• Establish clear plans for pilots, phased releases, state deployments, monitoring, support, and rollback.
• Ensure the team learns from production performance after release.
• Build the Product Practice
• Establish lightweight product practices appropriate for a lean, mission-driven, AI-enabled organization.
• Create clear standards for opportunity framing, discovery, prioritization, product briefs, roadmap communication, release readiness, measurement, and decision documentation.
• Use AI tools to accelerate research synthesis, product analysis, prototyping, documentation, testing, and routine coordination while maintaining human judgment and data safeguards.
• Help colleagues understand the difference among organizational strategy, program needs, product opportunities, features, and technical tasks.
• Create enough structure to produce clarity and accountability without introducing unnecessary bureaucracy.
• Help Think of Us develop the ability to evaluate and operate multiple products over time.
• Review feedback from Care Navigators and determine whether the underlying issue requires a product change, service change, training, or operational support.
• Write a product brief for an AI copilot, including what it does, what it does not do, the intended value, major risks, human-review expectations, and evaluation plan.
• Meet with the CEO to unpack a new strategic idea, clarify whether it is an exploration or direction, and return with a recommendation and clear tradeoffs.
• Work with the Lead Product & UX Designer to review research findings and determine whether they require a roadmap or service-model change.
• Review AI evaluation results with the Director of Data & AI and Senior Applied Data Scientist, then decide whether a feature is ready for limited release.
• Pair with the Principal Engineer to reduce scope when the original approach creates disproportionate technical, security, or maintenance risk.
• Talk with a state partner about an operational problem without immediately committing to the proposed solution.
• Review product and operational data from a recently released feature and decide whether to expand, revise, or stop it.
• Prepare a decision memo explaining why the team recommends delaying a promising idea to protect a more important outcome.
• Lead a release-readiness review covering design, technical quality, security, data, program practice, training, and implementation.

Requirements

• Eight or more years of product-management experience, including at least three to four years as a lead or highly senior product manager on software products.
• A demonstrated track record of shipping and improving software products rather than primarily managing programs, contracts, projects, or requirements documents.
• Experience owning meaningful product decisions, including roadmap prioritization, feature scope, release readiness, and cross-functional tradeoffs.
• Strong outcome orientation, including experience defining success, instrumenting products, interpreting evidence, and iterating based on real-world performance.
• Technical fluency sufficient to understand architecture tradeoffs, data flows, APIs, privacy and security implications, AI limitations, and technical specifications.
• Experience working closely with Design and Engineering from early problem framing through production release.
• Experience with AI-powered or probabilistic products where quality is difficult to define, trust must be earned, and human review is part of the product.
• Ability to distinguish among model quality, product quality, user experience, operational performance, and demonstrated impact.
• Experience navigating complex, multi-stakeholder environments involving technical, programmatic, operational, and external partners.
• Ability to translate ambitious and evolving executive ideas into structured product opportunities and clear recommendations.
• Experience working in an early-stage or resource-constrained environment where product practices had to be established rather than inherited.
• Experience working with or alongside systems that affect young people and families, or a deep commitment to learning about these systems with humility, curiosity, and care.
• Motivation to contribute to social impact and systems change while maintaining discipline about what technology can and cannot accomplish.
• Take ownership in a lean environment, set priorities, and move work forward without waiting for detailed direction.
• Engage confidently with active executive leadership without becoming passive or defensive.
• Listen for the strategic intent beneath evolving ideas and separate the underlying opportunity from an assumed solution.
• Distinguish brainstorming, recommendations, organizational direction, external commitments, and product decisions.
• Challenge assumptions respectfully using user evidence, operational context, technical realities, data, and clear reasoning.
• Make tradeoffs visible and state what must stop, move, or change when a new priority is introduced.
• Protect focus without becoming rigid or using product process to resist legitimate strategic change.
• Decide under uncertainty and know when a decision requires more evidence, broader consultation, or executive escalation.
• Communicate clearly in writing and in person, including when explaining what is not on the roadmap and why.
• Build alignment across Product, Design, Engineering, Data and AI, Program, Operations, Policy, and executive leadership.
• Move quickly without confusing urgency with haste.
• Use structure to create clarity, not bureaucracy.
• Bring sound judgment and genuine care to decisions that affect people navigating stress, crisis, and institutional systems.
• Take responsibility for decisions rather than allowing unclear consensus or endless consultation to substitute for ownership.
• Background in civic technology, social impact, healthcare, public benefits, human services, education, or another high-stakes environment.
• Experience working with government or state partners while maintaining a coherent product strategy.
• Familiarity with HIPAA, privacy, consent, accessibility, safeguarding, or other regulatory environments.
• Experience designing or operating human-in-the-loop AI systems.
• Experience with copilots, conversational products, AI agents, retrieval-augmented generation, or related AI-enabled workflows.
• Experience supporting products deployed across multiple jurisdictions or operating environments.
• Experience working on products that combine software, human services, staff workflows, and operational processes.
• Familiarity with product experimentation, AI evaluation, or mixed-method product measurement.
• Experience helping an organization move from one primary product toward a broader product portfolio.
• Experience using AI-assisted tools to accelerate product discovery, prototyping, analysis, documentation, and testing.

Skills

Required

• Product management
• Roadmap prioritization
• Feature scope definition
• Release readiness
• Cross-functional tradeoffs
• Outcome orientation
• Working with Design and Engineering
• AI-powered or probabilistic products
• Complex multi-stakeholder environments
• Social impact and systems change
• Ownership in lean environment
• Engaging with executive leadership

Preferred

• Human-in-the-loop AI systems

Benefits

• At TOU, we believe that taking care of our people is foundational to the impact we aim to make. Our compensation philosophy is rooted in transparency and a holistic understanding of people’s needs. We believe fair, market-competitive pay is essential to attracting and retaining the exceptional talent needed to achieve our ambitious goals. As a not-for-profit organization, we design our compensation packages—including both salary and benefits—with care and in alignment with our financial sustainability.
• The annual salary for this role is $150,000–$180,000. Starting salaries for new hires will be determined based on a combination of the new hire’s relevant experience and market demands.
• TOU’S benefits go beyond the basics. They’re designed to support your well-being, growth, and sense of purpose at work and beyond. From comprehensive health coverage to professional development support and meaningful time off, our benefits reflect our commitment to nurturing a workplace where people can thrive, both personally and professionally.
• Health & Insurance
• 100% employer-paid medical, dental, and vision coverage for employees; 50% for dependents.
• Access to Talkspace for confidential therapy and mental health support.
• Short-Term Disability, Life, and AD&D Insurance included.
• Optional Long-Term Disability and Supplemental Life Insurance.
• Health Care and Dependent Care FSAs available.
• Financial Benefits
• 401(k) Plan for pre-tax retirement contributions.
• Work-from-home setup stipend to optimize your workspace.
• Paid Time Off
• Flexible PTO policy, plus sick leave and paid leaves of absence.
• 8 company holidays, plus two organization-wide seasonal breaks.
• Learning & Development
• TOU values continuous learning and invests in the professional development of its employees in alignment with organizational needs based on role, performance, business needs, and Company policies.
• Regular organization-wide learning sessions on relevant and reflective topics.