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Trust \& Safety Remote (overlap with PST) Full\-time
Bluesky’s mission is to build an open protocol for the social internet. As Bluesky continues to grow and explore new product surfaces, Trust \& Safety needs to be embedded early in product strategy, design, and launch readiness.
We’re looking for a Senior Product Manager, Trust \& Safety and AI Safety to serve as the primary product partner between Trust \& Safety, Product, Engineering and Legal. This person will own our product risk assessment process, lead operational readiness for AI\-adjacent product work, and help ensure new features are built with safety considerations from the start.
This is a high\-context, cross\-functional role for someone who can move between strategy and execution: understanding emerging product risks, translating them into clear operational requirements, driving alignment across teams, and building repeatable systems that help Bluesky ship quickly and responsibly.
### Responsibilities:
- Own the Product Risk Assessment process end\-to\-end for new feature launches, including intake, scoping, risk categorization, mitigation tracking, launch readiness, and post\-launch review.
- Serve as the primary Trust \& Safety liaison to Product and Engineering for new product development, ensuring safety considerations are included early in specs, roadmap conversations, and launch planning.
- Lead Trust \& Safety product thinking for AI\-adjacent product work, including harm framework operationalization, launch readiness, tooling needs, queue impact, escalation paths, moderator training, and communications posture.
- Build and maintain repeatable launch readiness frameworks for Trust \& Safety, including checklists, templates, trackers, and feedback loops from post\-launch moderation and operational observations.
- Partner with Product, Engineering, Policy, Legal, Comms, and Operations to identify risks, define mitigations, and clarify ownership across complex or ambiguous product launches.
- Establish a forward\-looking roadmap for Trust \& Safety product needs, including internal tooling, AI safety capabilities, detection systems, queue routing, escalation infrastructure, reporting, and risk dashboards.
- Act as the Trust \& Safety product counterpart in roadmap reviews, product planning rituals, spec reviews, and launch readiness checks.
- Translate operational Trust \& Safety needs into product requirements that Engineering and Product can act on.
- Identify strategic opportunities where Trust \& Safety systems, automation, tooling, or process improvements can compound over time.
- Help move Trust \& Safety from a reactive review function to a proactive product partner embedded in how Bluesky builds.
### You might be a good fit if you:
- Have experience in product management, Trust \& Safety, integrity, platform safety, AI safety, risk, or a closely related field.
- Have worked on consumer products at scale, especially products with user\-generated content, social interactions, recommendations, messaging, AI features, or other high\-risk surfaces.
- Are strong at identifying product risks early and translating them into practical mitigations, operational requirements, and launch criteria.
- Can build systems from scratch: intake processes, risk assessment frameworks, launch readiness checklists, product requirements, trackers, and cross\-functional operating rhythms.
- Are comfortable working across Product, Engineering, Policy, Legal, Comms, and Operations, and can drive clarity when ownership is ambiguous.
- Have strong product judgment and can balance user experience, safety, operational feasibility, legal exposure, and company velocity.
- Are thoughtful about AI safety and can reason about how AI\-enabled features may create new forms of user harm, abuse, manipulation, operational burden, or regulatory risk.
- Communicate clearly in writing and can create crisp documentation that helps teams make decisions.
- Like working on small, fast\-moving teams with high autonomy.
- Are excited to help build the safety foundations for an open social protocol.
### Additional Information:
The anticipated base salary range for this position is $138,000 \- $186,000 USD excluding equity. Equity will be considered in the total compensation package. Final base salary for this role will be based on the individual’s geographic location, as well as experience level, skill set, training, licenses and certifications.
We’re a fully remote team, but meaningful overlap with Pacific Time working hours is required. For this role, proximity and willingness to travel to San Francisco, Seattle, or team offsites is a plus. We offer health, dental, and vision insurance.
If you believe the social web should be open, user\-controlled, and built with safety from the start, we’d love to hear from you.
Salary Context
This $138K-$186K range is below the median for AI Product Manager roles in our dataset (median: $188K across 140 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 3,708 AI roles we're tracking, AI Product Manager positions make up 5% of the market. At BlueSky | Craddock Oil, 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 in Demand for This Role
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 $216,175 based on 270 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $230,000. This role's midpoint ($162K) sits 25% below the category median. Disclosed range: $138K to $186K.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
BlueSky | Craddock Oil AI Hiring
BlueSky | Craddock Oil has 2 open AI roles right now. They're hiring across AI Product Manager, AI/ML Engineer. Based in US. Compensation range: $186K - $405K.
Location Context
AI roles in Austin pay a median of $214,343 across 87 tracked positions.
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 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 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 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). 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 (102) are outnumbered by mid-level (1,705) and senior (1,469) 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 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 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 $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. 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 $300,000 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 (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 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.
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