---
title: 'Platform Engineer, Application Security at METR'
canonical: 'https://feeny.ai/job/platform-engineer-application-security-metr-berkeley-w44zdwnsrdma'
type: 'job'
last_seen: '2026-10-16'
---

# Platform Engineer, Application Security at METR

- **Company:** METR
- **Location:** Berkeley
- **Compensation:** $328k–$579k
- **Work type:** onsite
- **Posted:** 2026-07-08
- **Last confirmed live:** 2026-10-16
- **Apply:** https://jobs.lever.co/metr/775fa999-229d-40c1-b5eb-53794c20ee60

## 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](https://metr.org/blog/2026-08-31-security-update/) 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.

- Offensive security: Experience with red teaming, penetration testing, and/or vulnerability research.

- 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 Requirements: Our technical team members are in our office in Berkeley 3-5 days/week. Please let us know in your application if this is a constraint. If you lack US work authorization and would like to work in-person (strongly preferred), 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.

## About METR

## Company Overview
- **One-liner**: METR (pronounced "meter") is a non-profit research organization that develops scientific methods to assess catastrophic risks from advanced AI systems by evaluating their autonomous capabilities.
- **Entity Type**: Non-profit (funded by donations, not a typical private company; no equity)
- **Headquarters**: Berkeley, California, USA
- **Founded**: Not explicitly stated, but founded by Beth Barnes; likely ~2021–2022
- **Founders**: Beth Barnes (Founder, CEO)

## Core Business
- **Primary industry**: AI safety research and evaluation
- **Target customers**: AI developers (e.g., OpenAI, Anthropic, Google DeepMind, Meta, Amazon), governments, and the broader public
- **Mission or purpose**: "Develop scientific methods to assess catastrophic risks stemming from AI systems’ autonomous capabilities and enable good decision-making about their development."

## Products & Services
- **Frontier AI Capability Evaluations**: Systematic assessments of how autonomously AI systems can perform tasks (e.g., conducting research, developing apps, cyberattacks, self‑hardening). Published as open research.
- **Risk Assessments & Safety Policies**: Advises AI developers and governments on risk assessment methodologies, including the "Responsible Scaling Policies" approach adopted by nine leading AI labs.
- **Time‑Horizon Research**: Open‑source analysis showing that the length of tasks AI agents can complete doubles every ~7 months, a key input for forecasting transformative AI timelines.
- **Evaluation Platform**: An open‑source platform built on Inspect AI for running AI agent evaluations at scale.
- **Monitorability Evaluations**: Research on detecting AI agents attempting to evade monitoring or perform side tasks, including datasets of "reward hacking" and "sandbagging" behaviors.
- **Productivity RCT**: A randomized controlled trial with experienced open‑source developers measuring how much AI tools actually boost productivity (finding systematic overestimation).

## Market Standing
- **Valuation/Market Cap**: Not applicable (non‑profit)
- **Key Metric**: Funding – METR is supported by donations from major foundations and individuals. Notable donors include The Audacious Project (TED), Jane Street, Sijbrandij Foundation, Pew Charitable Trusts, Schmidt Sciences, Packard Foundation, and others. Small part of income from a technical assistance contract with the European AI Office. **No funding from AI companies** (maintains independence).
- **Notable Investors/Partners**: Partners with OpenAI, Anthropic, Google DeepMind, Meta, Amazon (pilot risk assessments); member of NIST AI Safety Institute Consortium, California Cybersecurity Task Force, UK AI Security Institute; technical assistance to European AI Office.
- **Growth Signals**: Growing team (multiple open roles), expanding into cyberforensics and embedded assessments, research cited widely in AI safety policy, and adoption of their Responsible Scaling Policies by major developers.

## Competitive Advantages
- **Independence**: No funding from AI companies, enabling unbiased, transparent research.
- **Scientific Rigor**: Publishes all research openly; uses empirical methods (RCTs, time‑horizon analysis) rather than speculation.
- **Policy Influence**: Their frameworks (e.g., Responsible Scaling Policies) are now industry standards, and they advise governments globally.
- **Deep Technical Expertise**: Team of researchers and engineers building state‑of‑the‑art evaluations for autonomous capabilities, including security‑relevant evaluations.

## Strategic Focus
- **Current priorities**: Developing methodologies to track AI loss‑of‑control risk, improving monitorability evaluations, expanding cyberforensics capabilities, and scaling the team to meet growing demand for independent evaluations.
- **Direction for growth**: Increasing influence on AI governance, deepening partnerships with governments and companies, and building tools for continuous risk assessment.

## Why Work Here
- **Mission‑driven**: Direct contribution to aligning AI development with public safety, working on one of the most critical problems of our time.
- **Compensation**: Highly competitive with top AI labs (salary ranges $328K–$687K for technical staff, $150–$300/hr for contractors), plus benefits like medical/dental/vision, wellness ($1,500/yr), mental health ($6,000/yr), professional development ($5,250/yr), unlimited PTO.
- **Work environment**: Small, fast‑moving, mission‑driven team based in Berkeley. On‑site preferred for technical roles (at least a few days a week), but hybrid and remote (including international) can be accommodated. Operations roles require in‑person.
- **Hiring process**: Unique focus on work tests (1–3 take‑home tasks) and a 1–2 day paid work trial (travel and lodging reimbursed). Interviews are given substantially less weight. Commitment to diversity and equal opportunity.
- **Culture**: Open, transparent, and empirical; values rigor and independence. Visa sponsorship available for technical roles.

## Sources
1. [metr.org](https://metr.org/)
2. [metr.org/about](https://metr.org/about#our-team)
3. [metr.org/careers](https://metr.org/careers)
4. [metr.org/hiring](https://metr.org/hiring)
5. [jobs.lever.co/metr](https://jobs.lever.co/metr)

## Other roles at METR

- [Head of People](https://feeny.ai/job/head-of-people-metr-berkeley-w6nads6qcqmt) — Berkeley
- [Chief Information Security Officer](https://feeny.ai/job/chief-information-security-officer-metr-berkeley-v6sp1pxb2hs8) — Berkeley
- [Member of Technical Staff, Offensive Security Research](https://feeny.ai/job/member-of-technical-staff-offensive-security-research-metr-berkeley-kxzz3emzx9gj) — Berkeley
- [IT Systems Engineer](https://feeny.ai/job/it-systems-engineer-metr-berkeley-87zqbgq2ffsv) — Berkeley
- [Member of Technical Staff, Embedded Assessments](https://feeny.ai/job/member-of-technical-staff-embedded-assessments-metr-berkeley-jsprvy2fdmqy) — Berkeley
- [Member of Policy Staff, Government Affairs](https://feeny.ai/job/member-of-policy-staff-government-affairs-metr-washington-zyknyagdb3c7) — Washington, DC
- [Member of Technical Staff, Evaluation Execution](https://feeny.ai/job/member-of-technical-staff-evaluation-execution-metr-berkeley-rtt64jwna58y) — Berkeley
- [General Expression of Interest](https://feeny.ai/job/general-expression-of-interest-metr-berkeley-avs3pft13sf0) — Berkeley