Note: The job is a remote job and is open to candidates in USA. Future of Life Institute (FLI) is focused on addressing the risks posed by advanced AI systems. The AI Safety Argumentation Platform Research Engineer will develop and operate systems that integrate argumentation theory with AI tools to facilitate effective communication and understanding of AI risks.
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
Skills
- 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
Benefits
- This position is 100% remote but requires occasional travel.
- Candidates outside the U.S. would be engaged as independent contractors with project-focused responsibilities.
Company Overview