Staff+ Software Engineer, Account Compromise
full-time
lead
Posted 5 hours ago
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About this role
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
Anthropic's Safeguards organization builds the systems that keep Claude safe to use at scale. The Account Compromise team owns one specific slice of that work: protecting the people and organizations who use Claude from losing control of their accounts, and preventing compromised accounts and credentials from being used to abuse our platform. Account takeover, credential stuffing, phishing-driven session theft, leaked API keys, and resold access all cause real harm — to the customers whose accounts are hijacked, and to the wider ecosystem when stolen access is used to route abusive traffic through legitimate accounts.
We are looking for a staff+ engineer to set the technical direction for this work. You will own the architecture of how we detect, contain, and remediate account compromise across Claude and the Claude Developer Platform, making the design decisions that other engineers and teams build on top of. You will move between deep technical work and adversarial problem-solving: threat modelling how attackers will adapt, scoping multi-month projects from ambiguous starting points, and leading complex live investigations when they escalate.
This is a hard problem space. Attackers iterate quickly, the signals separating a compromised account from an unusual but legitimate one are subtle, and every defence carries a cost to real users if it fires incorrectly. You will be building the playbook, and the judgement calls about where to draw those lines will largely be yours to make and defend.
You will operate with high autonomy — owning detection coverage and incident leadership, driving alignment with Security, Product, and Policy teams, and shaping how Anthropic approaches this problem globally rather than executing against someone else's roadmap.
Key responsibilities
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
Design automated response flows that cut off attacker access while minimising disruption to legitimate users
Lead investigations into significant compromise incidents end to end, then convert what you learn into durable, automated defences
Threat model how attackers are likely to adapt, and prioritise the team's work against that view rather than only against incidents already observed
Drive cross-organisational alignment on account security direction with Security, Product, Support, Policy and other partners.
Define how the team measures success and hold the work to those measures
Set technical standards for the domain and raise the bar for other engineers through code review, design review, and mentorship
Surface patterns from compromise cases to research and product teams so that protections improve upstream
Minimum qualifications
10 + years experience designing, building, and operating detection, anti-fraud, anti-abuse, or security systems in production
A track record of independently scoping and delivering complex, ambiguous, multi-month technical projects
Experience making architectural decisions in an adversarial domain that other engineers and teams then build on
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
Ability to reason rigorously about large behavioural or telemetry datasets, and to distinguish attacker behaviour from unusual but legitimate use
Strong written communication and a track record of driving alignment across multiple teams and stakeholders
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
Preferred qualifications
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 with authentication and identity systems, including OAuth, single sign-on, multi-factor authentication, device binding, and risk-based authentication
Experience applying machine learning to fraud or abuse detection, alongside a clear sens
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