About Haven Safety
Haven Safety AI is building the enterprise learning intelligence layer for safety. Co-founded with The AES Corporation and AI Fund, the venture studio founded by Andrew Ng, Haven helps high-risk organizations learn faster from what goes wrong so they can prevent what comes next.
Haven works alongside existing EHS enterprise systems to improve how organizations investigate, assess, and learn from incidents. INVESTIGATE guides evidence synthesis, timeline development, multi-threaded causal analysis, and corrective actions. ASSURE continuously reviews completed investigations for evidence quality, causal coverage, guideline adherence, and CAPA strength. LEARN reasons across incident history to surface recurring control failures, repeated corrective-action patterns, CAPA debt, and emerging signals.
The platform combines current incident evidence, company knowledge, historical cases, and an industry knowledge graph. A coordinated team of specialized AI agents examines evidence, controls, engineering factors, procedures, regulations, training, and organizational history, then produces one traceable assessment for human review. Customers have reported an 80% reduction in root cause analysis labor time using Haven. About the Role:
You will work on the AI and LLM engineering layer that connects Haven’s evidence base and knowledge graph to the product experiences investigators and safety leaders use. This is a build-and-operate role reporting to the CTO. You will design the reasoning, ship it, instrument it, and improve it using production evidence.
The work is technically demanding and operationally consequential. Haven serves enterprise customers in regulated, safety-critical industries through multi-tenant and dedicated deployments. A plausible answer and a correct answer can look the same until someone acts on it, so precision, traceability, evaluation, and human oversight are core product requirements.
Haven Safety is a VC-backed pre-seed venture. This role will be a important member of the founding team and will require wearing multiple hats. This role is based in the US and relocation will not be considered.