Senior Software Engineer, Ontology & Reasoning Systems (819)

At Protegrity, we lead innovation by using AI and quantum-resistant cryptography to transform data protection across cloud-native, hybrid, on-premises, and open source environments. We leverage advanced cryptographic methods such as tokenization, format-preserving encryption, and quantum-resilient techniques to protect sensitive data. As a global leader in data security, our mission is to ensure that data isn’t just valuable but also usable, trusted, and safe.

Protegrity offers the opportunity to work at the intersection of innovation and collaboration, with the ability to make a meaningful impact on the industry while working alongside some of the brightest minds. Together, we are redefining how the world safeguards data, enabling organizations to thrive in a GenAI era where data is the ultimate currency. If you're ready to shape the future of data security, Protegrity is the place for you.

Role Overview

Protegrity is seeking a Senior Software Engineer, Ontology & Reasoning Systems to design and build the ontology and reasoning layer that connects structured sources, semi-structured metadata, and unstructured documents into a model that supports deterministic machine reasoning.

In this role, you will formalize complex domains into entities, relationships, constraints, and rules that allow the system to derive conclusions from underlying facts. A key focus will be making those conclusions explainable and traceable, with clear derivation paths back to the source data and logic that produced them.

LLMs play an important role at the ingestion boundary, supporting extraction, normalization, and categorization of information from unstructured or ambiguous inputs. The reasoning layer itself must remain deterministic, auditable, and explainable, with appropriate checks on model-generated outputs before they are used as trusted facts.

You will work closely with product and research teams to define formal models, improve reasoning quality, and build systems that support accurate, reviewable outputs. This role is well suited for someone with a strong foundation in logic, graph-based systems, formal modeling, and production-grade software engineering.

What You’ll Do

• Own the ontology and rule layer that unifies structured, semi-structured, and unstructured enterprise data into a single reasoning model.

• Model entities, relationships, events, and constraints across heterogeneous sources, and develop rules that derive conclusions from combinations of facts.

• Use LLMs at the ingestion boundary for extraction, normalization, and categorization, with appropriate validation of model-generated outputs.

• Make system findings traceable by connecting each conclusion to the source facts and rules that produced it.