[Hiring] Head of Neuro-Symbolic AI @Sapience AI Corporation

Role Description

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.

What you will own (Areas of Responsibility)

• Neuro-symbolic architecture and direction
  • 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.
• Reasoning over the knowledge graph
  • 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.
• Trust, explainability, and provenance
  • 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.
• Research direction and applied advances
  • 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.
• Team leadership
  • 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.
• Productionization with platform and applied AI
  • 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.
  • Turn architectural advances into dependable behavior in MINERVA.
• Evaluation and measurement
  • 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.

Required Qualifications

• Deep expertise in neuro-symbolic AI, knowledge representation, reasoning, or a closely related field.
• Experience combining symbolic methods with neural or language-model systems.
• A track record of turning advanced AI research into working systems.
• Strong grounding in knowledge graphs, retrieval, and modern LLMs.
• Experience leading researchers or engineers, or clear readiness to lead.
• Rigor about evaluation, groundedness, and honest handling of uncertainty.
• The ability to translate hard ideas for a broad technical audience.

Preferred Qualifications

• A graduate degree or equivalent depth in AI, machine learning, computational logic, or a related area.
• Publications, patents, or shipped systems in neuro-symbolic or knowledge-based AI.
• Experience with explainable AI and provenance.
• Experience productionizing reasoning systems at scale.
• Domain understanding of professional communities or knowledge-intensive organizations.

Skills & Competencies

• Neuro-symbolic architecture and knowledge representation.
• Reasoning over knowledge graphs, plus retrieval and inference.
• Fusing symbolic structure with neural and LLM methods.
• Explainability, provenance, and trustworthy AI.
• Evaluation design for reasoning quality and groundedness.
• Research leadership and productionization.
• Clear technical communication of complex ideas.

Services & Tools Experience

• Knowledge graph and symbolic reasoning systems, ontologies, and rule engines.
• Modern ML frameworks (PyTorch or equivalent) and LLM tooling.
• Retrieval, embeddings, and vector systems.
• Graph databases (for example Neo4j-class systems).
• Evaluation and experiment-tracking tooling.
• Python as the primary language.

Prior Experience & Background

• Prior senior work in neuro-symbolic AI, knowledge-based systems, or applied reasoning research.
• Experience shipping reasoning or knowledge systems in production.
• A background bridging research and engineering.
• Experience leading a team or a significant technical area is a plus.

Cross-functional partners

You work most closely with Research, Applied AI, Knowledge Graph Engineering, Platform Engineering, and Product. You are accountable for the COGENT architecture and how it turns the KO graph into reasoning members can trust inside MINERVA.

Compensation

• Base Salary: $216,000 - $240,000 + early stage equity
• Generous health and wellness benefits