Jobs at Apollo Research

Conduct fundamental AI safety research on reward-seeking, evaluation awareness, scheming, and misaligned preferences. Design and train model organisms, study reinforcement-learning dynamics, develop scalable evaluations, investigate frontier-model cognition, and establish scaling laws for scheming risks. Collaborate with leading AI labs and communicate findings through scientific writing and other media. The role requires empirical research ability, RL-trained LLM experience, strong quantitative analysis, conceptual creativity, and intensive engagement with AI progress.

Conduct embedded evaluations of frontier AI labs and models to assess alignment and loss-of-control risks. Responsibilities include analyzing messy datasets, identifying anomalous model behavior, researching scheming and reward-seeking, developing evaluation tools and playbooks, writing high-stakes reports, and managing ambitious projects under tight deadlines. Some candidates will work on-site with frontier AI labs, while others will support evaluations through applied research and tooling.

Conduct empirical AI safety research focused on designing, implementing, and evaluating monitoring and control protocols for coding agents. Responsibilities include building evaluation frameworks and datasets, fine-tuning open-source models, developing agentic monitoring systems, analyzing failure modes, and optimizing detection accuracy, cost, and latency for production use.

Develop threat models, kill chains, security levels, and failure-mode libraries for potentially adversarial coding agents. Design realistic attacks, adjudicate flagged agent behavior, red-team Watcher monitors, and build adversarial test suites. The role requires hands-on security experience, code and infrastructure understanding, technical threat modeling, strong research and writing skills, and comfort working independently on ambiguous problems.

Design, implement, and operate Apollo’s security controls across identity, cloud infrastructure, endpoints, and incident response. Build secure-by-default systems, evaluate security vendors, lead security projects, shape the roadmap, and promote effective security practices across the organization. Key initiatives include zero-trust migration, agentic SOC development, sandbox hardening, third-party access reviews, incident response, and penetration-testing tooling.

Secure Apollo’s internal software, infrastructure, and AI-agent environments through threat modeling, red teaming, attack-trajectory development, adversary tracking, and detection engineering. Own security findings through remediation by designing durable controls, automated tests, CI/CD integrations, and monitoring. Collaborate closely with engineers and research teams to address novel AI-agent and insider-risk threats while documenting threat models and failure modes clearly.

Lead and grow a product engineering team building Watcher, a coding-agent security product. Responsibilities include planning delivery, managing engineers, hiring, coordinating research and engineering handoffs, handling customer integrations, making architecture decisions, reviewing code, and shipping production code primarily in Python and TypeScript. This player-coach role also establishes engineering processes, protects team focus, and uses AI-assisted tools extensively.

Own customer deployments, integrations, technical evaluations, proofs of concept, and white-glove support for Watcher, a coding-agent security product. Build integrations with coding agents, SIEMs, identity systems, and CI/CD pipelines across cloud, on-premises, and self-hosted environments. Troubleshoot customer issues, tune security monitors, communicate with technical and security leaders, and convert recurring customer needs into reusable product capabilities, documentation, and deployment tooling.

Build and operate Watcher, a full-stack coding-agent security product. Develop backend APIs, ingestion and grading pipelines, agent hooks, CLI tooling, monitoring dashboards, enterprise integrations, and real-time blocking systems. Own features from customer discovery through production deployment, while ensuring reliability, scalability, tenant isolation, encryption, access controls, and flexible cloud, on-premises, and local deployments. Collaborate with customers and security teams to improve the product and productionize monitoring research.