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Job Description

About METR

We are a nonprofit research organization that develops scientific methods to assess AI capabilities, risks, and mitigations, with a specific focus on threats related to AI R&D automation and misalignment.

We believe it is robustly good for policymakers and civil society to have a clear understanding of risks from AI systems, and we are extremely excited to build a team of ambitious, excellent people to tackle one of the most important challenges of our time.

About the role

    METR’s mission of enabling transparency and coordination about the risks of frontier AI requires a high degree of trust from frontier AI labs, governments, and the public. As misalignment incidents become more extreme and confidential information about models and frontier AI labs becomes more valuable, we expect to be under increasingly intense pressure from external actors and internal agents. 

    METR is looking to expand the security expertise on our platform team. This would span application security in our evaluation platform, sandboxing agents and evaluations, cloud platform security, networking, access control for both people and agents, and securing our development environments and workflows. This role will have a large engineering component: expect to write and review code, fix vulnerabilities, and design and develop secure systems.

What this role looks like

  • Securing a unique attack surface. METR's evaluation infrastructure runs frontier AI agents, including early checkpoints of unreleased models, executing untrusted, model-generated code at scale on multi-day tasks. You will design and build the isolation, networking, and permission boundaries that contain evaluated agents. 

  • Remediation and hardening. You will find, triage, and fix vulnerabilities across our cloud infrastructure and access control systems.

  • Fixing known vulnerabilities in our codebase. This includes code reviews and resolving known vulnerabilities in our backlog.

  • Identity and access as a system. You will design and implement IAM policies, least-privilege access, and automated provisioning and access review for both people and agents.

  • Securing agentic systems. You will design and implement systems to monitor and control agents, making sure they can operate securely and with appropriate permissions and guardrails.

Required skills

  • 7+ years of experience working in security engineering, software development, or an adjacent field.

  • Production software engineering. You have experience building and operating backend or infrastructure in practice.

  • Cloud and container security. You have deep familiarity with AWS (especially non-trivial IAM), Kubernetes, and infrastructure-as-code environments.

  • Vulnerability remediation. You have found and fixed security flaws in large production systems and can prioritize a remediation backlog.

  • Security fundamentals. Strong security knowledge across systems, networks, cloud, and identity, and a track record of applying it to real systems. Experienced in designing secure software and cloud architectures.

  • Code review. Reviewing and giving constructive security feedback on PRs, including from the FOSS community.

  •  

Nice to haves

  • Detection engineering at scale: Experience with detection pipelines (DataDog SIEM, AWS SecurityHub), writing and tuning detections, and threat hunting. 

  • AI/LLM engineering: You build with AI: agent pipelines, LLM-powered tooling, automated workflows, and understand current limitations of those tools.

  • AI security research: Familiarity with agent control, hardware security, or red teaming AI systems themselves.

  •  

    Ideally you have experience with a portion of these technologies:

  • AWS: cloud-native software platforms

  • EKS

  • Lambda

  • ECS

  • IAM (in-depth)

  • CloudWatch

  • SecurityHub & GuardDuty

  • PostgreSQL: RLS, serverless Aurora

  • Pulumi: IaC

  • DataDog: SIEM

  • Okta: IdP

  • Google Workspace: IdP

  • Tailscale: networking

  • CrowdStrike Falcon: endpoint security

  •  

Our Culture
 
METR is a mission-driven organization. We believe our work can meaningfully shape humanity's future for the better, and we want to be the best people in the world doing this work. We have a tight-knit, collaborative research culture rooted in truth-seeking and integrity. We're fiercely committed to producing high-quality, trustworthy science. We're honest and transparent about our results, especially when they may go against the grain. We've earned trust as reliable partners who handle confidential information with care. We maintain a low-ego, drama-free environment focused on what matters.
 
Hybrid Preferred: Our technical team members are in our office in Berkeley 3-5 days/week. We would ideally like for you to be in person too, but we are happy to be flexible here. If you lack US work authorization and would like to work in-person, we can likely sponsor a cap-exempt H-1B visa for this role.
 
We encourage you to apply even if your background may not seem like the perfect fit! We would rather review a larger pool of applications than risk missing out on a promising candidate for the position.
 
We are committed to diversity and equal opportunity in all aspects of our hiring process. We do not discriminate on the basis of race, religion, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. We welcome and encourage all qualified candidates to apply for our open positions.
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  • Role Platform Engineer, Application Security
  • Experience 3-4 years
  • Work type Hybrid
  • Location United States
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METR
AI Research Lab · Berkeley, CA, United States

METR is a research nonprofit that evaluates frontier AI models to help companies and wider society understand AI capabilities and what risks they pose.

All jobs at METR
Job Overview

Approx. salary range

202K – 326K

Our estimate — this employer did not publish a salary

Our estimate, not the employer’s. Worked out from the middle half of 40 comparable roles on Neural Jobs that did publish a salary, in the same field, country and experience band. The real figure for this job may be different.

Eligibility
United States Right to work in the United States required.
Workplace
Hybrid
Job Posted:
2 months ago
Job Type
Full Time
Experience
3-4 years

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