Staff+ Software Engineer (Account Compromise)

Join Anthropic, a leading AI safety and research company. As a Staff+ Software Engineer in the Account Compromise team, you will set the technical direction for account security, design detection systems, lead investigations, and drive cross-organizational alignment. You will operate with high autonomy and have a significant impact on the safety and integrity of our platform.

• Set the technical direction and own the architecture for account compromise detection, response, and remediation across Claude and the Claude Developer Platform.
• Independently scope and lead complex, multi-month engineering projects from an ambiguous starting point through to production systems that operate reliably under adversarial pressure.
• Build and evolve detection systems that identify account takeover, credential abuse, and compromised API keys in near real time.
• Ability to reason rigorously about large behavioural or telemetry datasets, and to distinguish attacker behaviour from unusual but legitimate use
• Sound judgement about the tradeoff between stopping bad actors and disrupting legitimate users, and the ability to explain and defend where you have drawn that line
• 10 + years experience designing, building, and operating detection, anti-fraud, anti-abuse, or security systems in production
• Strong written communication and a track record of driving alignment across multiple teams and stakeholders
• A track record of independently scoping and delivering complex, ambiguous, multi-month technical projects
• Proficiency in Python and SQL, with strong software engineering fundamentals and hands-on coding ability
• Experience leading investigations into account-based abuse or security incidents, and translating findings into automated detection
• Experience making architectural decisions in an adversarial domain that other engineers and teams then build on
• Significant engineering experience in trust and safety, platform integrity, fraud, or detection and response, including time as a technical lead or mentor
• Deep familiarity with account attack techniques
• Experience applying machine learning to fraud or abuse detection, alongside a clear sense of when simpler rules-based approaches are the better choice
• Experience with authentication and identity systems, including OAuth, single sign-on, multi-factor authentication, device binding, and risk-based authentication
• Experience with cloud data tooling such as BigQuery, Spark, dbt, Airflow or similar
• Experience building tooling for operational or investigative teams, and partnering closely with the people who use it
• Interest in AI safety, and in the specific ways account compromise intersects with model misuse
• 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
• We encourage you to apply even if you do not believe you meet every single qualification