Working familiarity with formal or semi-formal argumentation theory (abstract or structured argumentation, defeasible reasoning, dialectical models, or argumentation schemes)
Experience with ontology engineering or knowledge graph development (OWL/RDF, property graphs, or equivalent)
Operational experience with LLM agent systems: agent coordination platforms, prompt engineering at scale, and QC regimes for LLM outputs (adversarial probing, consistency checks, calibration)
Fluent vibecoding practice: rapid prototyping and shipping with LLM-assisted development in production-adjacent contexts
Substantive grounding in AI safety, AI governance, and current frontier-AI dynamics, with the literacy to locate authoritative sources on any sub-topic or human expertise in the space
Familiarity with philosophy of science concepts bearing on evidence: defeaters, burden of proof, inference to the best explanation, underdetermination
Good coding skills; comfort with graph databases or query languages
Experience designing cross-check and verification scaffolds for unreliable automated processes
Sound judgment about when a claim is well-supported versus when it needs hedging, further substantiation, or withdrawal
Self-directed; strong written communication
Graduate work or equivalent depth in argumentation theory, computational argumentation, epistemology, or philosophy of science
Familiarity with AIF, Carneades, or comparable computational argumentation tools
Track record in AI safety or governance (publications, policy work, or substantive community contributions)
Background in argument mining, claim extraction, or stance detection
Experience with debate formats or structured deliberation methods
Understanding of motivated reasoning, belief change, and cognitive biases as they bear on communications strategy
Open-source contributions in any relevant area
$160,000 - $210,000 a year