Senior AI Engineer

Alice's RL Environments team builds adversarial environments that the world's leading AI labs use to test and train their most capable agents. Each environment is a working replica of a real system with an attack planted inside it. A verifier decides whether the agent held up. The environments run on AgenticVerse, our platform for building and running RL environments at scale. A large and fast-growing community of researchers works on it every day. We're looking for a Senior AI Engineer to own those environments and the evaluation that decides which tasks are good enough to train a frontier model. What you'll do RL environments Build RL environments end to end: the replica systems, the planted attack, and the verifier that grades the run Own environment and verifier design for tool-use, web, and computer-use agents Make environments airtight: sandboxed, free of eval-awareness cues, and closed to reward hacking Read rollout traces, find where the agent took a shortcut, and close it Task evaluation Own Alice's proprietary task evaluator, the engine that decides whether a task is ready for a frontier lab Make it the industry's sharpest quality bar for RL tasks: realism, threat-model accuracy, and training value Keep it learning: every customer review and every post-training run makes it stricter Run infrastructure Scale the run pipeline: queue-driven runners on Kubernetes, per-run sandboxes, and a grader the agent can't reach Package environments so they drop into customer training and evaluation pipelines Working with Research Work with researchers as one team, from a task idea to an environment that's ready to train on Turn what post-training runs reveal into fixes in the environments Review designs and code, and raise the engineering bar for the people around you What we're looking for 6+ years as a backend engineer, building production systems BSc in Computer Science or a related field, preferably from a leading university Strong Python, and production experience with Docker, Kubernetes, and cloud infrastructure (AWS preferred) Experience designing distributed systems and message queues A track record of owning systems from design to production High autonomy in an undefined space. You take a loose problem and come back with working code Fluent written and spoken English Advantage Academic background in AI or machine learning: a degree, thesis, or research Hands-on AI engineering: building with LLMs, agents, or evaluations Exposure to post-training: RL fine-tuning, reward design, or rollout analysis Background in security, red teaming, or trust and safety Alice is a trust, safety, and security company built for the AI era. We safeguard the communicative technologies people use to create, collaborate, and interact- whether with each other or with machines. In a world where AI has fundamentally changed the nature of risk, Alice provides end-to-end coverage across the entire AI lifecycle. We support frontier model labs, enterprises, and UGC platforms with a comprehensive suite of solutions: from model hardening evaluations and pre-deployment red-teaming to runtime guardrails and ongoing drift detection. Alice is widely considered a global leader in online safety and AI security. We have some of the most forward-thinking and passionate minds in the world working to safeguard over 3 billion users across the largest AI and tech platforms. If you're creative and driven to secure the future of AI, we want to hear from you!