Research Scientist/Engineer – Agentic Systems

White Circle; Paris; Sur place; EUR 60 000 - 90 000; Plein temps

Avantages offerts par ce poste

Paid time off

Comprehensive medical insurance

Covered subscriptions for AI tools

Team off-sites twice a year

Résumé du poste

White Circle in Paris is seeking a research scientist to build large-scale environments for testing LLM agents. You will conduct experiments to observe and catalogue agent failures, contributing to the development of AI safety protocols.

The ideal candidate has experience in empirical research and software engineering, preferably holding a MSc or PhD in a related field. The position is hybrid, with a relocation package available for qualified candidates.

Qualifications

• Experience in building non-trivial agent environments or automated research pipelines.
• Strong software and AI engineering capabilities.
• Experience with empirical research methodologies.
• Ability to define research questions and turn them into experiments.
• Fluent with AI models and coding.

Responsabilités

• Build adversarial environments for agents.
• Catalogue concrete agent failure modes.
• Run experiments with external APIs and internal models.
• Build realistic multi-agent environments.
• Turn findings into public writeups.

Connaissances

Agent environment development

Software engineering

Empirical research

AI model usage

Research pipeline orchestration

Formation

MSc or PhD in a related field

Outils

Python

AI frameworks

Description du poste

TLDR: We’re looking for a research scientist to build autonomous, large-scale environments that push LLM agents (single and multi-agent) to failure, and study how they actually break.

About us

White Circle is an AI Safety company building the safety, reliability, and optimization layer for AI systems. At the core of our platform are policies – simple natural-language rules that define what an AI model should and shouldn’t do. We automatically test, enforce, and continuously improve these policies at scale.

• We’ve raised $11M from top funds, founders, and senior leaders at OpenAI, Anthropic, HuggingFace, Mistral, DeepMind, Datadog, Sentry, and others
• We process over 100M+ API calls every month
• We fine-tune and train our own LLMs so they run faster and cheaper than any open or proprietary model

We’re a small, highly focused team. If you want to work deeply on hard problems, see your work ship to production quickly, and influence how AI safety is actually built – you’re the one we need.

About the team

White Circle's fundamental research team works on the science of how AI systems fail: where agents break, why misalignment and unsafe behaviours emerge, and how to catch them before they reach the real world. We build the evals, benchmarks, environments, and tooling that empirically study the most pressing AI safety concerns — some of which become the guardrails shipped in our products, and some of which become public writeups.

You will

• Build adversarial environments for agents: complex, uncertain settings that sit on the boundary of agent capability and alignment, where failure is informative rather than trivial.
• Build realistic multi-agent environments and instrument them so emergent breakdowns are observable — failures that arise from the agents themselves, not ones scripted from the outside.
• Run experiments end to end, against external APIs and our own models, orchestrating many agents in parallel.
• Catalogue concrete agent failure modes and build the tooling to surface them at scale.
• Turn findings into internal models of agent behaviour and into public writeups.

You’ll fit right in if you

• Have built at least one non-trivial agent environment or automated research pipeline that ran end to end (single- or multi-agent), and can talk through what broke and why.
• Strong software and AI engineering. Can independently orchestrate many agents and containers in parallel without that orchestration being the bottleneck.
• A track record of empirical research in agents, red-teaming, or post-training where you defined the question, ran it, and drew a defensible conclusion.
• A fast empirical iterator who is comfortable defining the question when there's no playbook: can take a fuzzy concern ("do these agents collude under pressure?") and turn it into a concrete, falsifiable experiment.
• An AI power-user — fluent with frontier models and coding agents in your daily work.

A big plus

• Published research at A* venues on automated red-teaming, agentic environments, or post-training.
• Experience building monitoring for model failures and anomalous behaviour.
• Experience reproducing public benchmark results and finding where the original methodology is fragile or misleading.
• An MSc or PhD in machine learning, computer science, cognitive science, computational neuroscience, physics, or a related quantitative field.
• AI safety fellowship (MATS, ASTRA, Anthropic Fellows, etc.), or a comparable self-directed research record.

Why White Circle

• Paid time off in line with your local regulations, no matter where you work from
• Work from Paris (hybrid) with a relocation package available, or work from London (note: we are unable to provide relocation support or medical insurance for London-based roles)
• Comprehensive medical insurance for our France-based team
• All the hardware, tools, and services you need
• Covered subscriptions for AI agents and IDEs
• Team off-sites twice a year: we’ve recently been to the Alps and to Saint-Tropez