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About This Role
The National Center on Sexual Exploitation (NCOSE) is a national nonprofit organization working to prevent sexual abuse and exploitation mass scale by eliminating institutional behaviors & cultural norms that enable it. Through advocacy, education, research, communications, and strategic partnerships, NCOSE works to advance policies, practices, and cultural change that protect human dignity and promote healthier communities.
The NCOSE Parent Center is a key part of this work, equipping parents and caregivers with practical resources, education, and support to help children navigate an increasingly sexualized and digital world. The Parent Center helps families understand emerging risks, have meaningful conversations with children, and take informed action to create safer environments for young people.
Position Overview
The National Center on Sexual Exploitation (NCOSE) is seeking a Senior Technical Product Manager to lead the development, beta testing, launch, and continued evolution of an innovative AI-powered Parent Center focused on helping parents, caregivers, and communities protect children in an increasingly complex digital environment.
This is not a traditional project management position.
We are looking for a hands-on product leader who understands how modern software is built, has successfully helped bring technology products to market, and can operate effectively between organizational leadership, users, subject-matter experts, and an external software development team.
Experience launching AI or LLM-powered products is strongly preferred.
The successful candidate will become NCOSE's day-to-day product owner for the Parent Center and will initially lead an important beta deployment involving schools and real-world users.
This person must be technically fluent enough to challenge developers, evaluate technical recommendations, understand AI system limitations, identify product risks, and hold an external development firm accountable for quality, schedule, and results.
Key Responsibilities
Product Leadership
Own the Parent Center product from beta through broader deployment.
Translate NCOSE's vision, child-safety expertise, stakeholder requirements, and user feedback into actionable product requirements.
Develop and maintain the product roadmap, backlog, user stories, priorities, acceptance criteria, and release schedule.
Serve as the primary day-to-day product contact between NCOSE leadership and the external development team.
Ensure that technology decisions remain aligned with the mission and intended purpose of the Parent Center.
Beta Program
Design and manage the Parent Center's initial school beta program.
Develop structured beta-testing protocols, success metrics, feedback mechanisms, and launch criteria.
Coordinate onboarding and communication with participating schools and users.
Analyze qualitative and quantitative feedback and translate findings into product improvements.
Maintain clear reporting on beta performance, adoption, user experience, defects, risks, and development progress.
AI Quality & Evaluation
Develop a repeatable evaluation framework for the Parent Center's AI system.
Create and maintain test suites covering normal user interactions as well as difficult, ambiguous, adversarial, and high-risk situations.
Evaluate areas including:
- Response accuracy and usefulness
- Hallucinations and unsupported claims
- Source quality
- Consistency
- Appropriate escalation
- Child-safety scenarios
- Crisis and emergency situations
- Sextortion
- Grooming
- Pornography exposure
- Sexting and explicit-image situations
- Social media and gaming platforms
- School-device concerns
- Prompt injection and adversarial behavior
- AI-generated sexual exploitation concerns
- Privacy and data handling
- Guardrails and system boundaries
Partner with NCOSE subject-matter experts to ensure the system accurately reflects organizational guidance and child-safety best practices.
Establish measurable release thresholds rather than relying solely on subjective assessments that the AI "looks good."
Development & Vendor Management
Manage NCOSE's relationship with the external development firm at the product level.
Hold the development team accountable for:
- Deliverables
- Engineering estimates
- Timelines
- Product quality
- Defect resolution
- Documentation
- Release readiness
Review proposed technical solutions and ask informed technical questions.
Identify unclear estimates, unnecessary complexity, product risks, technical debt, and potential gaps between requirements and delivered functionality.
Ensure fixes are validated through regression testing before release.
Launch & Product Operations
Develop formal criteria for moving from:
Internal Testing School Beta Expanded Pilot Production Launch
Establish dashboards and reporting covering product health, AI quality, user feedback, open defects, critical issues, development velocity, and launch readiness.
Lead post-launch product monitoring and continuous improvement.
Help NCOSE develop a long-term strategy for additional AI and digital products.
Technical Fluency
You do not need to be a software engineer.
However, you must be technically fluent enough to communicate effectively with engineers and evaluate technical decisions involving areas such as:
- Modern web applications
- APIs and integrations
- Cloud infrastructure
- Databases
- Authentication and authorization
- Analytics and telemetry
- Software development lifecycle
- QA and automated testing
- AI/LLM systems
- Prompt engineering
- Retrieval-Augmented Generation (RAG)
- Model evaluation
- AI guardrails
- Hallucination mitigation
- Observability
- Security and privacy
You should be comfortable asking a development team to explain an architecture or estimate and capable of recognizing when the explanation is inadequate.
Qualifications
Required
- 6+ years of product management, technical product management, software product leadership, or closely related experience
- Demonstrated experience taking a meaningful technology product through development, beta/pilot, and launch
- Strong technical fluency and experience working directly with software engineering teams
- Experience managing external technology vendors and/or distributed engineering teams
- Experience developing product requirements, user stories, acceptance criteria, roadmaps, and release plans
- Strong QA and analytical mindset
- Ability to communicate technical issues clearly to nontechnical executives and stakeholders
- Strong organizational skills and personal accountability
- Ability to operate effectively in a mission-driven organization where the consequences of poor product decisions can be significant
Strongly Preferred
- Direct product experience with generative AI or LLM-powered applications
- Conversational AI or chatbot experience
- Experience with RAG, AI evaluation frameworks, model testing, guardrails, or AI observability
- Experience conducting AI red-team or adversarial testing
- EdTech or K-12 technology experience
- Trust & Safety experience
- Child-safety technology experience
- Digital health or other high-stakes technology experience
- Experience with privacy-sensitive or regulated products
Who Will Succeed Here
We're interested in people who ask difficult questions.
If a developer says something will take six weeks, you want to understand why.
If an AI system produces the correct answer 19 times and a dangerous answer the twentieth time, you don't consider the problem solved.
If a product works perfectly during a demonstration but fails under unusual real-world conditions, you want to know about those conditions before our users discover them.
You should be comfortable telling organizational leadership when a product isn't ready to launch—and equally comfortable telling a development team when their work doesn't meet agreed-upon requirements.
You should enjoy building systems, solving difficult problems, testing assumptions, and turning complicated technology into products that real people can confidently use.
Why This Role Matters
Children and parents are navigating rapidly evolving technologies, platforms, social networks, AI tools, and online risks.
The Parent Center is intended to provide parents and caregivers with practical, accessible guidance when they need it—including during situations that can be confusing, frightening, or urgent.
That creates an unusually high standard for the technology behind it.
NCOSE is looking for someone who wants to help us meet that standard.
This position initially centers on successfully bringing the Parent Center through beta and launch, but it also represents an opportunity to help shape NCOSE's broader AI and digital product strategy.
Working Environment/Physical Requirements
- This is a hybrid position in the DC Office or optional remote. Individuals will be required to sit for long periods, stand, or walk as needed. Also, light lifting - up to 15 pounds.
- For remote positions, the individual must work in a quiet space - no background noise - and have the camera turned on during all calls and meetings.
- Local travel to meetings, including walking or taking an uber or cab. Occasional out of town travel may be required.
Compensation & Benefits
Salary is commensurate with experience with a range of $140,000–$165,000. Exceptional candidates may be considered above the posted range.
Benefits include generous medical, dental, vision insurance, FSA, 401K, paid time off, and EAP.
To Apply:
Click "Apply for this Job" at the top of this screen to submit your application. Please include your resume, cover letter, and references.
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About NCOSE
NCOSE is passionate about building a diverse team (and movement) committed to a world free from sexual abuse and exploitation. We love people and fight for the human dignity of all. We have a global and multicultural impact. Our work is premised on the following principles.
- We view the commodification of people for sex as inherently harmful,
- We support laws which seek to decrease and ultimately end demand by strongly penalizing those who pay to use the bodies of other people for sex,
- We work to create robust services for those seeking freedom from organized systems of sexual exploitation,
- We prevent sexual exploitation by opposing policies and reforming systems which facilitate harm, and
- We support legal reforms that decriminalize victimization.
Our Mission
Prevent sexual abuse and exploitation mass scale by eliminating institutional behaviors & cultural norms that enable it.
Our Vision
The National Center on Sexual Exploitation (NCOSE) believes in a world free from sexual abuse and exploitation. We believe every human being deserves the opportunity to live life to its fullest potential: to pursue dreams; express creativity and hone talents; seek beauty, truth, and faith; experience hope, joy, and love with family and friends—to thrive. Such a vision requires not only individuals and institutions that work towards its realization, but also a culture that embraces its responsibility to preserve and protect human flourishing. We aspire to create that culture.
How Do We Behave?
- Unifying – We love people and partnerships.
- Aspiring – Being in this work is a deep-seated calling to justice.
- Unrelenting – With hope, we persevere with enduring determination.
- Dignifying – We recognize and uplift the inherent human dignity of all.
- Innovating – We seek thoughtful, inventive, cutting-edge tactics and methods.
- Inspiring – We elevate others with our vision and coalesced passion.
Our Approach
NCOSE inspires society to end sexual abuse and exploitation through corporate advocacy, public policy, research, training, litigation, and by catalyzing a global movement to defend human dignity.
If you share our principles and hope for a world where everyone has the opportunity to thrive, come put your mind, background, and experience to work for us!
Salary Context
This $140K-$165K range is in the lower quartile for AI Product Manager roles in our dataset (median: $187K across 155 roles with salary data).
View full AI Product Manager salary data →Role Details
About This Role
AI Product Managers define what AI features get built and why. They translate business problems into ML-solvable tasks, work with engineering to scope model requirements, and own the metrics that determine if an AI feature is working. The role requires a rare combination of technical fluency and product instinct.
Unlike traditional product management, AI PM work involves managing uncertainty at a fundamental level. Your model might work 90% of the time. What happens the other 10%? What's the user experience when the AI is wrong? How do you measure 'good enough' for a probabilistic system? These questions don't have easy answers, and the AI PM is the person responsible for finding them.
Across the 11,520 AI roles we're tracking, AI Product Manager positions make up 4% of the market. At National Center on Sexual Exploitation, this role fits into their broader AI and engineering organization.
AI Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.
What the Work Looks Like
A typical week includes: reviewing model evaluation results with the ML team, defining success metrics for a new AI feature, conducting user research on how customers respond to AI-generated outputs, writing product requirements that include accuracy thresholds and fallback behaviors, and presenting the AI roadmap to leadership. You're the translator between technical capability and business value.
AI Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.
Skills Required
Technical fluency with ML concepts is essential, though you won't be writing models. Expect to understand training data, evaluation metrics, model limitations, and responsible AI practices. SQL and basic Python are increasingly expected. Experience with A/B testing, data analysis, and product analytics is baseline. Understanding LLM capabilities and limitations is now a core requirement.
The differentiator is AI-specific product thinking: knowing when to use ML vs. heuristics, understanding the cost of training data collection, designing graceful degradation for model failures, and building products that improve with usage data. Experience with AI safety, bias mitigation, and responsible AI deployment is increasingly important.
Strong postings describe specific AI products the PM will own, mention the ML team structure, and talk about measurement methodology. Look for companies that have already shipped AI features. Roles at companies that are 'exploring AI' often mean you'll spend a year defining the strategy before any building happens.
Compensation Benchmarks
AI Product Manager roles pay a median of $220,200 based on 993 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $230,000. This role's midpoint ($152K) sits 31% below the category median. Disclosed range: $140K to $165K.
Across all AI roles, the market median is $213,480. Top-quartile compensation starts at $264,000. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($266,050) and AI Engineering Manager ($253,461). By seniority level: Entry: $112,320; Mid: $193,200; Senior: $230,000; Director: $272,250; VP: $235,830.
National Center on Sexual Exploitation AI Hiring
National Center on Sexual Exploitation has 1 open AI role right now. They're hiring across AI Product Manager. Based in Washington, DC, US. Compensation range: $165K - $165K.
Location Context
Across all AI roles, 6% (708 positions) offer remote work, while 10,737 require on-site attendance. Top AI hiring metros: New York (3,257 roles, $221,000 median); San Francisco (2,766 roles, $260,550 median); Los Angeles (1,580 roles, $210,000 median).
Career Path
Common paths into AI Product Manager roles include Product Manager, Data Analyst, Technical Program Manager.
From here, career progression typically leads toward Director of AI Product, VP Product, Head of AI.
The most effective path is PM experience plus self-directed AI education. Take Andrew Ng's courses, build a small ML project, and learn enough Python to read model evaluation code. The goal isn't to become an ML engineer. It's to have credibility in technical conversations and to understand what's possible, what's hard, and what's a bad idea.
What to Expect in Interviews
AI interviews typically combine coding challenges (Python-focused), system design questions tailored to the role, and discussions about your experience with relevant tools and frameworks. Strong candidates demonstrate both technical depth and the ability to make pragmatic engineering tradeoffs. Prepare portfolio projects that demonstrate end-to-end capability rather than isolated skills.
When evaluating opportunities: Strong postings describe specific AI products the PM will own, mention the ML team structure, and talk about measurement methodology. Look for companies that have already shipped AI features. Roles at companies that are 'exploring AI' often mean you'll spend a year defining the strategy before any building happens.
AI Hiring Overview
The AI job market has 11,520 open positions tracked in our dataset. By seniority: 140 entry-level, 5,630 mid-level, 4,176 senior, and 1,574 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (708 positions). The remaining 10,737 roles require on-site or hybrid attendance.
The market median for AI roles is $213,480. Top-quartile compensation starts at $264,000. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($266,050 median, 70 roles); AI Engineering Manager ($253,461 median, 58 roles); Research Engineer ($252,000 median, 476 roles).
AI Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.
The AI Job Market Today
The AI job market spans 11,520 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (8,769), AI Software Engineer (586), AI Product Manager (511). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (140) are outnumbered by mid-level (5,630) and senior (4,176) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 1,574 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (708 positions), with 10,737 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $213,480. Top-quartile roles start at $264,000, and the 90th percentile reaches $318,400. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $266,050 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (2,267 postings), Aws (1,178 postings), Azure (972 postings), Rag (924 postings), Gcp (715 postings), Pytorch (586 postings), Claude (572 postings), Kubernetes (559 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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