Technical Program Manager, Safeguards - Launches

About Anthropic

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.

About the Role

As a Technical Program Manager for Safeguards focused on model launches, you'll be the critical bridge between Research, Inference, Product, and Safety teams during our highest-stakes model and product releases. You'll drive end-to-end execution of Safeguards deployment for model and product launches, ensuring our safety classifiers are properly configured, deployed, tested, and scaled across all platforms while balancing capacity constraints, performance requirements, and user experience considerations.

Responsibilities:

• Own end-to-end safeguards readiness for model launches - Drive all safeguards deployment activities from pre-launch planning through post-launch stabilization, ensuring classifier systems are properly configured, tested, and scaled for each new model release
• Coordinate complex cross-platform deployments - Manage classifier rollouts across platforms, each with distinct infrastructure constraints, capacity requirements, and deployment timelines
• Make real-time technical trade-off decisions - Balance competing constraints around classifier capacity, latency impacts, false positive rates, and robustness requirements during fast-moving launch cycles with aggressive timelines
• Drive capacity planning and performance optimization - Partner with Inference teams to model compute requirements, optimize classifier configurations (batch sizes, mesh topologies, chip allocation), and ensure we stay within overhead budgets while meeting safety requirements
• Lead launch day war room coordination - Serve as primary safeguards point of contact during launches, coordinating monitoring, troubleshooting classifier issues, and driving go/no-go calls on deployment decisions
• Build detailed execution plans and run-of-show - Create comprehensive launch checklists covering classifier configurations, monitoring thresholds, alerting setup, rollback procedures, and cross-team dependencies
• Partner with product teams on co-launch coordination - Ensure new product surfaces have appropriate safeguards protections configured, tested, and deployed; whether launching independently or alongside new models
• Monitor and respond to false positive patterns - Track flag rates across customer segments, identify problematic patterns, coordinate with research teams on classifier retraining priorities, and manage exemption processes for enterprise customers
• Manage transition to business-as-usual operations - Once launches stabilize, coordinate handoff of ongoing monitoring and optimization work to sustaining engineering teams, then move to the next model or product launch as needed
• Maintain technical documentation - Document classifier deployment configurations, capacity estimates, performance benchmarks, and lessons learned to build institutional knowledge

You may be a good fit if you:

• Have deep technical program management experience in ML/AI systems - Several years coordinating complex deployments involving model inference, distributed systems, and real-time production services at scale
• Have experience with AI safety or Trust & Safety - Familiar with concepts like false positive/false negative trade-offs, adversarial robustness, content moderation systems, or similar safety-critical technical systems
• Can navigate high-ambiguity technical challenges - Synthesize incomplete information from multiple engineering teams, identify critical path blockers, and drive decisions when faced with competing technical constraints and tight deadlines
• Excel at rapid decision-making under pressure - Comfortable making high-stakes trade-off decisions with incomplete information during time-critical launch windows, balancing safety requirements against capacity, latency, and user experience constraints
• Are skilled at cross-functional coordination in complex technical environments - Proven track record managing programs spanning research, infrastructure, safety, security, and product teams, navigating competing priorities and driving alignment
• Can communicate technical concepts clearly across varying levels of seniority - Equally comfortable explaining classifier handoff latency to product managers, debating capacity trade-offs with infrastructure teams, and briefing executives on launch readiness
• Are comfortable with on-call and launch coverage - Willing to provide real-time support during launch windows (including early morning/late evening as needed) and maintain availability for time-sensitive decisions

Deadline to apply: None. Applications will be reviewed on a rolling basis. 

Logistics

Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience.

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.

How we're different

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.

Come work with us!

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