Head of Neuro-Symbolic AI

Where this role sits

This role owns the heart of how Sapience AI reasons. You lead the neuro-symbolic approach that combines symbolic knowledge, structure, and rules with neural and language-model capability, the approach that lets the platform reason over a community’s expertise with both flexibility and rigor.

You own the direction of the COGENT architecture: how it fuses the KO (knowledge object) graph and symbolic reasoning with neural models, how it stays trustworthy and explainable, and how it advances over time.

You lead a specialized team and partner across research, applied AI, and knowledge graph engineering to turn a hard idea into a working system at the center of MINERVA.

Pure neural systems are fluent but can be confidently wrong, and they struggle to explain themselves. Professional communities cannot act on answers they cannot trust or trace. Collective intelligence needs reasoning that is both flexible and grounded.

Bringing symbolic structure and neural capability together is one of the hardest and most valuable problems in applied AI. It is also the core of what makes Sapience AI different.

The Head of Neuro-Symbolic AI owns that problem. You set the architectural direction, lead the team, and are accountable for reasoning that members can trust, trace, and act on.

You hold seven areas of responsibility across the neuro-symbolic architecture. Each one is yours to set direction on, build, and be accountable for.

• Own the direction of the COGENT architecture and how it fuses symbolic reasoning with neural and language-model capability.
• Set the approach to grounding, structure, and rules that keeps reasoning trustworthy.
• Decide what belongs in the symbolic layer, the neural layer, and the seam between them.

• Own how COGENT reasons over the KO graph to turn a community’s expertise into answers members can act on.
• Partner with knowledge graph engineering on the structures reasoning depends on.
• Advance retrieval, inference, and symbolic reasoning together, not in isolation.

• Make reasoning explainable and traceable, so members can see why the platform says what it says.
• Build the guardrails and provenance that let communities trust and verify answers.
• Reduce confident errors, and handle uncertainty honestly.

• Set the research agenda for neuro-symbolic methods at Sapience AI.
• Decide which advances are ready for production and which need more work.
• Keep the approach current with the field without chasing every trend.

• Build and lead a specialized team of researchers and engineers.
• Set a high bar for rigor and for shipping, and hold both.
• Grow the people who will define this area for the company.

• Partner with platform and applied AI to run neuro-symbolic reasoning reliably and affordably in production.
• Balance ambition against the constraints of latency, cost, and scale.

• Own how the quality of reasoning is measured, including accuracy, groundedness, and trust.
• Build evaluation that reflects what communities actually need, not just benchmark scores.
• Use evidence to steer the architecture’s direction.

You lead work at the frontier of applied AI, and you use AI throughout it, to explore approaches, run experiments, and reason about results, while holding the rigor that this domain demands.

The standard is human in partnership: AI accelerates the work, you own the judgment, the interpretation, and the call. The people who create the most value here are not the ones…