Future of Life Organizations - AI Safety Argumentation Platform Research Engineer
Requirements
• 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
Responsibilities
• Extend ontologies and knowledge graph schemas representing claims, evidence, argument structures, defeaters, and confidence • Implement defeasible argumentation frameworks (e.g., ASPIC+, Dung-style, argumentation schemes) that capture both logical structure and vulnerability to rebuttal • Operate and quality-control LLM-driven population pipelines, with cross-check scaffolds, provenance tracking, and human-in-the-loop curation • Architect agent coordination patterns for multi-step research and population tasks, with robust error handling and graceful degradation • Pre-harden argument structures by mapping the strongest counterarguments, steel-manned objections, and known defeaters • Build export pipelines that translate structured argumentation into diverse communications formats across audiences and registers • Maintain current awareness across AI safety, capabilities, and governance sufficient to know when new developments require graph updates, and to know where to find authoritative further detail • Collaborate with communications staff and researchers to ensure outputs serve real persuasive needs • $160,000 - $210,000 a year
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