Software Engineer, Safeguards Evals

Anthropic$320K — $485K *
Enterprise Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • Proficient in Python and experienced in software engineering across the stack.
  • Hands-on experience with data pipelines and large dataset management.
  • Familiarity with large language models (LLMs) and agentic systems, particularly their limitations.
  • Strong analytical skills for extracting actionable insights from extensive datasets.
  • Proven ability to shift between rapid prototyping and production-grade coding.
  • Capable of converting abstract problems into practical, experimental frameworks.

Responsibilities

  • Develop and manage a comprehensive evaluation framework for an AI investigative system.
  • Create real-world-based evaluation datasets representing various misuse scenarios.
  • Assess agent performance critically, focusing on detection precision and robustness.
  • Identify and address measurement gaps to enhance the evaluation process continuously.
  • Integrate research findings into continuous regression and release processes for system updates.
  • Design tools for policy experts to independently conduct evaluations.
  • Establish reinforcement learning environments to enhance safety checks in AI systems.

Benefits

  • Flexible work schedule with a hybrid office policy.
  • Opportunities for professional development and further education.
  • Access to robust resources for innovative research and development.
  • Collaboration with leading experts in AI safety and technology.
  • Visa sponsorship for eligible candidates.
Full Job Description
About the role How do we know our safety systems actually catch misuse? Anthropic increasingly uses AI to investigate potential misuse of Claude - analyzing real-world traffic to surface bad actors, policy violations, and emerging threats. Its findings inform enforcement actions and model launch decisions, which means we need rigorous, trustworthy answers to questions like: Does the monitoring agent catch what it should? Where does it fail? Does it stay reliable as adversaries adapt, as models improve, and as the agent itself changes? This role builds the evaluation infrastructure that answers those questions. You'll sit at the intersection of applied ML research and engineering - designing experiments to measure how well an investigative agent performs across harm areas, building datasets that represent real abuse rather than synthetic benchmarks, and shipping those methods into pipelines that gate every change to the system. Your work directly determines how much trust Anthropic can place in its automated abuse detection, and where we invest to make it better. Key responsibilities • Build and own the evaluation harness for an agentic investigation system - defining metrics, test cases and grading approaches for a complex long horizon agent • Construct high-quality eval datasets representing real-world misuse across harm areas (e.g., cyber attacks, bio weapons, influence operations), drawing from real traffic patterns and synthetic generation • Measure agent performance end-to-end (detection precision/recall, investigation quality, robustness) and drive hill-climbing on the hardest harm areas • Analyze coverage to identify measurement gaps, and evolve evals so they remain unsaturated and high-signal as agent capabilities advance • Productionize successful research into regression and release pipelines that run on every agent change, prompt update, and underlying model upgrade • Build tooling that enables policy experts to author, run, and iterate on evaluations without engineering support • Construct RL environments to improve Claude's safety investigation capabilities. Minimum qualifications • Proficiency in Python and comfort working across the stack • Experience building and maintaining data pipelines • Experience working with LLMs and a working understanding of their capabilities and failure modes - especially agentic systems with tool use and multi-step reasoning • Strong data analysis skills - you can draw reliable insights from large datasets • Ability to move fluidly between research prototyping and production-quality code • Ability to translate ambiguous problems into concrete, testable experiments Preferred qualifications • 6+ years of industry software engineering experience • Expertise in building or contributing to agent evaluation frameworks, benchmarks, or automated grading systems • Extensive experience in trust and safety, content moderation, or abuse detection systems • Experience in red teaming, adversarial testing, or jailbreak research on AI systems • Experience with synthetic data generation or data augmentation • Experience with distributed systems or large-scale data processing • Experience with prompt engineering or building LLM-powered applications 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: $320,000-$485,000 USD Logistics 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.

About Anthropic

Anthropic is an artificial intelligence research lab that focuses on developing AI systems that are safe, reliable, and trustworthy. The company was founded in 2019 by Dr. Yoshua Bengio, a leading AI researcher and winner of the Turing Award. Anthropic's research is focused on developing AI systems that can learn from small amounts of data, reason about complex systems, and interact with humans in a natural way. The company is based in New York City and has a team of experienced AI researchers and engineers.
Learn more about Anthropic
Size
50 employees
Industry
Founded
2019

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