정신 건강 관련 가이드라인을 설계하고, 콘텐츠 검토 운영을 관리하며, 데이터 분석을 통해 AI 모델의 성능을 개선하는 업무를 수행해요. 신뢰 및 안전(Trust & Safety) 분야의 실무 경험과 SQL 활용 능력이 필수예요. 업무 특성상 성적, 폭력적, 심리적으로 불안정한 콘텐츠에 노출될 수 있음을 인지해야 해요. 사무실 주 25% 이상 출근이 요구되는 하이브리드 근무 형태예요.
Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.
As a Safeguards Analyst on the User Well-being team, you will be focused on supporting the design and deployment of mental health guardrails – iterating on detection systems, managing review queues, evaluating new interventions, and monitoring existing ones. Interventions range from steering how Claude responds in the conversation itself to in-product features that connect users to other resources. This work involves translating expert clinical guidance, internal data analyses, and legal or engineering constraints into concrete changes to how we detect, review, and respond.
This team covers a broad set of interconnected harms including suicide, self-harm, disordered eating, AI sycophancy, and emotional dependence on AI. This position may expand into broader areas of user well-being enforcement over time. Safety is core to our mission, and you'll help shape policy enforcement so that our users can safely interact with and build on top of our products in a harmless, helpful, and honest way.
*Important context for this role: In this position you may be exposed to and engage with explicit content spanning a range of topics, including those of a sexual, violent, or psychologically disturbing nature.
Support the design and execution of interventions, defining key metrics, and curating evaluation datasets
Partner with Engineering and Data Science teams to build, tune, and validate detection models for automated intervention systems, including threshold-setting and precision and recall tradeoffs
Monitor how interventions and detection systems perform over time
Review flagged content to drive enforcement and policy improvements
Support the development of in-product features that connect users to crisis resources, working with Product, Legal, and external partners on referral pathways and user-facing content
Support the Safeguards Policy Design team by providing detailed feedback on policy gaps based on real scenarios
Keep up to date with emerging AI policy and external research on AI's relationship to mental health, and use these to inform our decision-making and workflows
Experience in trust & safety, product policy, content moderation, or a related field, with direct exposure to mental health, suicide and self-harm, or related well-being harm areas
Experience designing or running experiments, evaluations, or measurement studies to determine whether an intervention worked
Experience translating policy definitions into measurable form — the rubrics, review guidelines, or classification criteria, whether applied by human reviewers or automated systems
Experience managing or coordinating content review operations, including quality assurance and workflow management
Proficiency in SQL and/or other data analysis tools to measure intervention efficacy, monitor workflow health, and surface policy gaps
Experience working with generative AI products, including writing effective prompts for content review, classification, or evaluation
Experience turning open questions and data into concise and insightful analysis
Experience identifying emerging risks and communicating findings to cross-functional stakeholders
Understanding of the challenges involved in implementing product policies at scale in the content moderation space
Sound judgment in ambiguous, high-consequence cases, and comfort making a call and escalating appropriately when the available signal is incomplete
Subject matter expertise in mental health, whether developed in academia, clinical practice, crisis intervention, trust & safety, or other related settings
Experience building or evaluating LLM-based classification systems
Experience using agentic tools (e.g. Claude Code) to scale analysis or automate recurring work
Experience working within crisis support
The annual compensation range for this role is listed below.
For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.
Annual Salary:
$245,000—$285,000 USD
Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience
Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience
Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position
Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.
We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.
Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings.
We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.
The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.
