AI Safety Argumentation Research Engineer

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🕒 May 23

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Future of Life Institute (FLI)

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2014

🤖 Artificial Intelligence

🧬 Biotechnology

🤝 Non-profit

💰 $482.5k Grant on 2021-11

Artificial Intelligence • Biotechnology • Non-profit

Future of Life Institute (FLI) is a non-profit organization dedicated to steering transformative technologies, such as artificial intelligence and biotechnology, towards benefiting life and minimizing large-scale risks. The Institute focuses on cause areas like artificial intelligence, biotechnology, and nuclear weapons, advocating for policy changes and public awareness to mitigate associated risks. FLI engages in policy advocacy, outreach, grantmaking, and hosting events to discuss safe development and governance of these technologies. It collaborates internationally with entities like the United Nations and the European Union to ensure that powerful technologies are harnessed for positive future outcomes.

📋 Description

• 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

🎯 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.