In A Nutshell
Guide products from concept through launch and ongoing iteration, build the internal product function, and help NDWA understand and respond to emerging technology trends — including AI — shaping the care economy.
Responsibilities
Build a Movement-Centered Product Culture
- Champion a user-centered, experimental, and worker-driven product approach across NDWA.
- Shape the long-term product vision for NDWA’s digital initiatives, worker tools, and supporter-facing products.
- Develop intermediate and long-term plans for experimentation, learning, iteration, and continuous improvement.
- Apply an intersectional IDEAS lens to product decisions, ensuring that domestic workers — especially immigrant women and women of color — are centered in product research, testing, and experience design.
Technical Leadership & Architecture
- Own the technical vision and architecture strategy for NDWA’s digital products.
- Conduct regular code reviews and provide technical mentorship to engineering contractors (and eventually team).
- Write code regularly to maintain technical credibility and contribute to critical features, and add capacity to the team.
- Lead technical due diligence when evaluating vendors, contractors, and technical partner,s including technical interviews and code quality assessments.
Lead Product Strategy, Systems & Protocols
- Own product lifecycle strategy — from discovery and hypothesis setting to development, testing, launch, and iteration.
- Define and manage the product roadmap, prioritizing the highest-impact opportunities.
- Create and maintain systems for product planning, agile workflows, documentation, QA, and cross-team communication.
- Establish NDWA’s standards for experimentation, success metrics, usability, technical quality, and organizational alignment.
- Ensure seamless coordination across staff, contractors, and development partners.
Product Quality, Governance & Best Practices
- Ensure NDWA’s products are stable, secure, accessible, and well-structured for scalability.
- Develop governance practices for product decision-making, risk mitigation, and data/privacy compliance in collaboration with Data and Legal.
- Oversee reporting, dashboards, and systems that track product performance and user outcomes.
- Document key systems, processes, and architectural decisions to support institutional knowledge and the long-term sustainability of the product function.
- Make informed decisions about technical debt, prioritization, and system scalability based on hands-on technical assessment.
Strengthen NDWA’s Product & Technology Stack
- Oversee design and development of the Membership Center and Ask Aya through final build, testing, launch, and iteration phases.
- Partner closely with engineering, AI specialists, and external vendors to ensure efficient and high-quality execution.
- Evaluate and refine NDWA’s product and technology infrastructure, including architecture, integrations, and tech stack choices.
- Identify areas for innovation — particularly AI — that advance worker power, protections, or access to information.
Team Leadership
- Manage and develop a growing number of direct reports on the product team as well as the broader cross-functional team that touches the Membership Center and Ask Aya products, with responsibility for coaching, performance, recruitment, and talent development.
- Establish clear systems for coordination, communication, workflows, and accountability.
- Collaborate across teams to build shared understanding of product strategy and translate organizational needs into actionable product plans.
- Lead the handoff and transition planning with current leadership to ensure continuity of knowledge and systems.
- Mentor engineers of product thinking and while building the technical fluency of the product teams.
Skillset
- 8+ years of product and engineering experience, including at least 3-5 years in hands-on engineering roles and 3+ years leading product strategy. Must demonstrate progression from engineering to product leadership while maintaining technical fluency.
- Experience managing cross-functional teams and collaborating with engineering, design, content, organizing, and/or data teams.
- Strong strategic thinking combined with tactical execution — someone who balances long-term vision with day-to-day decision-making.
- Excellence in synthesizing insights, prioritizing ruthlessly, and designing experiments rooted in learning goals.
- Highly organized and operationally rigorous, with systems to prevent things from slipping through the cracks.
- A “head, heart, hands” leader: data-informed and analytical; empathetic, inclusive, and self-aware; courageous and action-oriented.
- Skilled relationship builder who practices “power with,” uses FAIR process, and contributes to a leadership culture centered on equity.
- Ability to communicate clearly with technical and non-technical audiences.
- Continuous learner with curiosity about emerging technologies (including AI) and their impact on workers.
- Proven track record of leveraging AI coding assistants and automation tools to increase personal productivity and team velocity over the past 2+ years.
- Commitment to economic, racial, and gender justice and experience working with diverse staff and worker communities.
- Proficiency in modern web development (JavaScript/TypeScript, React, Node.js, or similar).
- Experience with APIs, database design, and system architecture.
- Demonstrated use of AI coding assistants (Copilor, Cursor, Claude etc).
- Ability to write technical documentation, review code and debug issues independently.
- Understanding of cloud infrastructure (AWS), DevOps, and scalability considerations.
- Product management tools and workflows (agile, roadmapping, experimentation frameworks).
- Experience working with or managing engineering teams or contractors (preference for an engineering background, but not essential for the right candidate).
- UX/UI design familiarity — enough to guide design and assess usability.
- Understanding of data-informed product development and experiment design.
- Experience with AI tools, ethical considerations, or applied AI product development is a strong plus.
- Ability to quickly learn technical systems, evaluate architecture choices, and troubleshoot issues in partnership with developers.