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Standards Program Manager (Youth AI Safety Institute)
Common Sense Media is the leading nonprofit organization dedicated to improving the lives of kids and families by providing the research\-backed information, education, and independent voice they need to thrive in the age of apps, algorithms, and AI. We rate, educate, and advocate for policies to protect and prepare kids online. Our ratings, research, and resources reach more than 150 million users globally, over 1\.4 million educators, and more than 100,000 schools worldwide every year. Learn more at commonsense.org.
The Opportunity
Launched in May 2026, the Youth AI Safety Institute is Common Sense Media's newest addition to its programmatic pillar. The Institute establishes safety standards, builds open\-source evaluations that AI developers can run against their models, independently tests AI products, and publishes the results to provide transparency and accountability. It is an independent research and testing ground dedicated to ensuring the AI that children use is safe and developmentally appropriate.
The Standards Program Manager will plan, coordinate, and sustain the Institute's multi\-stakeholder input processes: the convenings, working groups, and expert sessions through which the Institute gathers the input needed to develop and evolve its AI safety standards. This is a high\-volume, high\-organization role that requires someone who can manage complex logistics, think strategically about participant engagement, and maintain active relationships with working group members between events.
The Standards Program Manager is not the primary facilitator in these sessions. That responsibility is shared by the Head of AI \& Digital Assessments and other senior Institute staff. Rather, this person ensures that every convening is well\-designed, well\-staffed, and set up for success: the right people in the room, a clear agenda, and strong follow\-through on what comes out of it. This role operates in close coordination with the Head of AI \& Digital Assessments and the Standards Analyst, and is essential to the Institute's ability to run a credible, transparent, and high\-quality standards\-setting process.
Location: San Francisco, California
Reports To: Head of AI \& Digital Assessments
Salary: $90,000\-$110,000
Type: Full\-time, exempt
What You'll Do
Convening Planning \& Logistics
- Plan and execute a high volume of convenings across multiple formats, including kickoff sessions, closed\-door expert roundtables, and technical working groups with industry representation.
- Manage all logistical elements of each convening: invitations, scheduling, venue or virtual platform coordination, travel arrangements, reimbursements, materials preparation, and participant communications.
- Develop and maintain systems and timelines to manage multiple concurrent convenings at different stages of planning and execution.
- Coordinate with Institute staff and organizational partners to ensure convenings are appropriately resourced and supported.
Participant Strategy \& Invitation
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- In collaboration with the Head of AI \& Digital Assessments and other Institute staff, contribute informed recommendations on who should be invited to each convening and why, with attention to expertise, perspective, stakeholder balance, and the specific goals of each session.
- Maintain an evolving roster of potential participants (including subject matter experts, field practitioners, researchers, advocates, and industry representatives) and help the Institute think strategically about participant mix across its portfolio of input processes.
- Draft and send invitation communications that clearly represent the Institute's purpose, independence, and expectations for participation.
Agenda Development \& Session Preparation
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- In collaboration with the Head of AI \& Digital Assessments and other facilitators, help design agendas that are appropriately scoped, sequenced, and calibrated to the goals of each session.
- Prepare session materials, including briefing documents, discussion guides, background readings, and participant bios.
- Ensure facilitators and Institute staff are well\-prepared for each session with the context and materials they need.
Stakeholder Relationship Management
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- Serve as a consistent point of contact for working group members and participants between convenings, maintaining active and professional relationships on behalf of the Institute.
- Track commitments, action items, and follow\-up items emerging from each session, and ensure they are appropriately routed and resolved.
- Circulate materials, summaries, and updates to participants in a timely and organized manner.
- Help the Institute maintain its credibility and relationships with a broad and diverse participant community over time.
Program Tracking \& Reporting
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- Maintain clear records of convening activity, participant engagement, and working group status across the Institute's standards program.
- Track and report on program milestones, upcoming convenings, and open action items for the Head of AI \& Digital Assessments.
- Identify and flag logistical or relationship issues early, before they become problems.
What We're Looking For
Required Qualifications
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- Education: Bachelor's degree in a relevant field (public policy, communications, nonprofit management, or related).
- Experience: 3–5 years of experience in program coordination, project management, or stakeholder engagement, preferably in a research, policy, or mission\-driven organizational context.
- Event \& Convening Management: Demonstrated experience planning and executing professional convenings, roundtables, or multi\-stakeholder meetings, including logistics, communications, and follow\-through.
- Relationship Management: Proven ability to manage ongoing professional relationships with diverse external stakeholders in a way that reflects well on the organization.
- Organizational Excellence: Exceptional attention to detail and project management skills, with the ability to manage multiple concurrent workstreams without dropping balls.
- Communication: Strong written and verbal communication skills, with the ability to represent the Institute professionally in external correspondence.
Preferred Qualifications
- Experience supporting standards\-setting, policy development, or advisory processes in a multi\-stakeholder environment.
- Familiarity with AI safety, technology policy, or child and youth safety issues.
- Experience working with technical or expert communities (researchers, industry professionals, policymakers).
- Background in stakeholder or community engagement in a research or advocacy context.
- Experience working in mission\-driven or nonprofit organizations.
Core Competencies
- Organizational Mastery: Manages complexity across multiple simultaneous workstreams with precision and calm.
- Strategic Thinking: Understands the purpose behind the logistics. Contributes meaningfully to participant strategy and session design, not just execution.
- Relationship Orientation: Builds and sustains professional relationships with a wide range of stakeholders, representing the Institute with consistency and care.
- Proactive Communication: Keeps all relevant parties informed, follows up without being asked, and flags issues before they escalate.
- Collaborative Approach: Works fluidly across internal teams and with senior staff.
- Adaptability: Comfortable operating in a fast\-moving, high\-volume environment where priorities and timelines shift.
What We Offer
- The chance to work with talented, passionate professionals.
- A great health and welfare benefits package, including medical, dental, vision, a matching 401(k), and other key benefits.
- An organization that offers work/life balance.
- The opportunity to really make a difference in the lives of kids and families!
*Common Sense Media provides equal employment opportunities to all qualified individuals and prohibits discrimination and harassment of any type without regard to race, color, religion, sex, gender identity, sexual orientation, pregnancy, age, national origin, physical or mental disability, military or veteran status, genetic information, or any other protected classification or characteristic protected by federal, state, or local laws.*
*Common Sense Media will also consider for employment qualified applicants with arrest and conviction records. However, job offers are made on the condition that the applicant subsequently passes a criminal background check. If the background check indicates a prior criminal conviction, we will conduct an individualized assessment to determine whether the conviction should result in denial of employment. Pursuant to the San Francisco Fair Chance Ordinance, we will consider employment for qualified applicants with arrest and conviction records.*
Salary Context
This $90K-$110K range is below the median for AI Safety roles in our dataset (median: $209K across 13 roles with salary data).
Role Details
About This Role
This role sits at the intersection of AI and engineering, building systems that bring machine learning capabilities into production environments. The scope varies by company, but the common thread is applying AI technology to solve real business problems at scale. Most AI roles today require a combination of software engineering fundamentals and domain-specific ML knowledge, with the exact mix depending on the team's maturity and the product they're building.
The AI job market is evolving fast. New role categories emerge as companies figure out what they need to ship AI-powered products. What matters most is the ability to learn quickly, build working systems, and iterate based on real-world performance data. The specific title matters less than the skills you bring and the problems you can solve. Companies are past the experimentation phase and want engineers who can deliver production-quality systems that work reliably at scale.
Across the 3,823 AI roles we're tracking, AI Safety positions make up 0% of the market. At Common Sense Media, this role fits into their broader AI and engineering organization.
AI hiring keeps growing across industries. Companies in tech, finance, healthcare, and retail are all building AI teams. The strongest demand is for people who can bridge the gap between AI research and production engineering. The shift toward generative AI has created new role types (LLM Engineer, Prompt Engineer, AI Agent Developer) that didn't exist three years ago, while traditional roles (Data Scientist, ML Engineer) have evolved to incorporate LLM capabilities.
What the Work Looks Like
Day-to-day work involves a mix of building, debugging, and collaborating. You'll write code, review pull requests, participate in design discussions, and work with cross-functional teams (product, design, data) to define what AI features should do and how they should behave. Expect to spend time on both technical implementation and communication. Most AI teams operate in two-week sprint cycles, with regular demos and retrospectives. The ratio of heads-down coding to meetings and reviews varies by seniority, with senior roles spending more time on architecture decisions and mentorship.
AI hiring keeps growing across industries. Companies in tech, finance, healthcare, and retail are all building AI teams. The strongest demand is for people who can bridge the gap between AI research and production engineering. The shift toward generative AI has created new role types (LLM Engineer, Prompt Engineer, AI Agent Developer) that didn't exist three years ago, while traditional roles (Data Scientist, ML Engineer) have evolved to incorporate LLM capabilities.
Skills in Demand for This Role
Python and cloud platform experience are common requirements. Specific skill needs vary by company and focus area, but familiarity with ML frameworks, data pipelines, and API design covers the basics for most roles. RAG (Retrieval-Augmented Generation), vector databases, and LLM API integration are increasingly standard requirements across role types.
Beyond the core stack, communication skills matter more than many technical candidates realize. The ability to explain AI capabilities and limitations to non-technical stakeholders is a differentiator at every level. Technical writing, documentation, and clear thinking about tradeoffs are underrated skills in AI roles. Experience with evaluation methodology (how to measure whether an AI system is working well) is becoming a core requirement, especially for roles that involve LLM integration.
Look for job postings that specify the problems you'll work on, the tech stack, and the team structure. Vague postings that list every AI buzzword are often a sign the company hasn't figured out what they need. Strong postings describe the product context, the team you'd join, and the specific challenges you'd tackle.
Compensation Benchmarks
AI Safety roles pay a median of $274,200 based on 55 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $165,000. This role's midpoint ($100K) sits 64% below the category median. Disclosed range: $90K to $110K.
Across all AI roles, the market median is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($275,000) and Research Engineer ($260,000). By seniority level: Entry: $97,880; Mid: $165,000; Senior: $227,400; Director: $247,800; VP: $250,000.
Common Sense Media AI Hiring
Common Sense Media has 4 open AI roles right now. They're hiring across AI Safety. Based in San Francisco, CA, US. Compensation range: $82K - $110K.
Location Context
AI roles in San Francisco pay a median of $253,000 across 2,168 tracked positions. That's 26% above the national median.
Career Path
Common paths into AI Safety roles include Software Engineer, Data Scientist, Data Analyst.
From here, career progression typically leads toward Senior Engineer, AI Architect, Engineering Manager, Principal Engineer.
Focus on building things that work. A deployed project that solves a real problem is worth more than any certification. Contribute to open-source, build portfolio projects, and invest in fundamentals (software engineering, statistics, systems design) rather than chasing the latest framework. The AI field moves fast, but the engineers who succeed long-term are the ones with strong fundamentals who can adapt to new tools and paradigms as they emerge.
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: Look for job postings that specify the problems you'll work on, the tech stack, and the team structure. Vague postings that list every AI buzzword are often a sign the company hasn't figured out what they need. Strong postings describe the product context, the team you'd join, and the specific challenges you'd tackle.
AI Hiring Overview
The AI job market has 3,823 open positions tracked in our dataset. By seniority: 112 entry-level, 1,798 mid-level, 1,516 senior, and 397 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (590 positions). The remaining 3,217 roles require on-site or hybrid attendance.
The market median for AI roles is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($275,000 median, 41 roles); AI Safety ($274,200 median, 55 roles); Research Engineer ($260,000 median, 434 roles).
AI hiring keeps growing across industries. Companies in tech, finance, healthcare, and retail are all building AI teams. The strongest demand is for people who can bridge the gap between AI research and production engineering. The shift toward generative AI has created new role types (LLM Engineer, Prompt Engineer, AI Agent Developer) that didn't exist three years ago, while traditional roles (Data Scientist, ML Engineer) have evolved to incorporate LLM capabilities.
The AI Job Market Today
The AI job market spans 3,823 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,629), Data Scientist (322), AI Software Engineer (279). 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 (112) are outnumbered by mid-level (1,798) and senior (1,516) 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 397 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (590 positions), with 3,217 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 $200,100. Top-quartile roles start at $253,500, and the 90th percentile reaches $307,500. 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 Engineering Manager roles lead at $275,000 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 (1,979 postings), Aws (1,190 postings), Azure (899 postings), Rag (839 postings), Gcp (726 postings), Pytorch (595 postings), Prompt Engineering (595 postings), Claude (540 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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