Head of Engineering, Research

Head of Engineering (Research)

FAR.AI is seeking a Head of Engineering (Research) to scale one of the world's leading AI safety research teams through a critical growth phase. You will instill excellent people and project management systems to enable our team to rapidly test and iterate on new ideas while maintaining high quality. You will scale the team from three to five research pods, expanding from 15 to 30 technical staff.

You will be the key glue that streamlines internal partnerships with other FAR.AI divisions, and manage key relationships with external stakeholders we work with including leading AI companies and government AI safety institutes. We expect this role’s primary focus to be building, managing, and scaling (90%) the technical team with minimal individual contributor (IC) or engineering focused work (10%). This role would be perfect for an experienced technical leader looking to work in an impact-driven environment.

FAR.AI is a non-profit AI research institute dedicated to ensuring advanced AI is safe and beneficial for everyone. Our mission is to facilitate breakthrough AI safety research, advance global understanding of AI risks and solutions, and foster a coordinated global response.

Since our founding in July 2022, we've grown quickly to 30+ staff, producing over 40 influential academic papers, and establishing leading AI Safety events. Our work is recognized globally, with publications at premier venues such as NeurIPS, ICML, and ICLR, and features in the Financial Times, Nature News and MIT Technology Review.

We drive practical change through red-teaming with frontier model developers and government institutes. Most recently, we discovered major issues with Anthropic’s latest model the same day it was released, and worked with OpenAI to safeguard their latest model. Additionally, we help steer and grow the AI safety field through developing research roadmaps with renowned researchers such as Yoshua Bengio; running FAR.Labs,

an AI safety-focused co-working space in Berkeley housing 40 members; and supporting the community through targeted grants to technical researchers.

Our research team likes to move fast. We explore promising research directions in AI safety and scale up only those showing a high potential for impact. Unlike other AI safety labs that take a bet on a single research direction, FAR.AI aims to pursue a diverse portfolio of projects. Our model is to conduct initial investigations into a range of high-potential areas.

We incubate the most promising directions through a combination of in-house research, field-building events, and targeted grants. Once the core research problems are solved, we work to scale them to a minimum viable prototype, demonstrating their validity to AI companies and governments to drive adoption.

Our current focus areas include:

• Mitigating AI deception
  : studying when lie detectors induce honesty or evasion, and developing model organisms for deception and sandbagging
• Evaluating and red-teaming
  :
  Conducting pre- and post-release adversarial evaluations of frontier models (e.g. Claude 4 Opus, ChatGPT Agent, GPT-5); developing novel attacks to support this work; and exploring new threat models (e.g. persuasion, tampering risks).
• Robustness
  : working to rigorously solve these security problems through building a science of security and robustness for AI, from demonstrating superhuman systems can be vulnerable through to scaling laws for robustness.
• Explainability
  : developing foundational techniques such as codebook features and AC/DC, and applying them to understand core safety problems like learned planning.

FAR.AI is one of the largest independent AI safety research institutes, and is rapidly growing with the goal of diversifying and deepening our research portfolio. For that reason, we’re seeking a Head of Engineering (Research) to manage the team, accelerate delivery, and grow the team to continue to scale our impact.

This role is critical to FAR.AI's mission. Our research directly influences how the most capable AI systems are developed and deployed. You will determine whether we can scale fast enough…