Sr Software Engineer - Knowledge Representation (Healthcare AI)

TL;DR

Sr Software Engineer - Knowledge Representation (AI): Designing and implementing ontological structures and knowledge graphs for the healthcare supply chain with an accent on AI integration and data-driven curation. Focus on building scalable structures to capture multimodal data and integrating LLMs with graph databases to ensure information transparency and explainability.

Location: Remote or Office-based in the USA

Salary: $114,000 - $152,000

Company

A healthcare business and data automation company providing a cloud-based supply chain technology exchange platform to maximize efficiency and accuracy in patient care.

What you will do

• Design and maintain ontologies and data architectures to represent complex relationships and entities within the healthcare supply chain.
• Lead the development of scalable databases to capture, store, and query structured, semi-structured, and unstructured multimodal data.
• Integrate graph solutions (RDF, LPG) with other data stores and technologies to support AI solutions.
• Leverage LLMs, GenAI, and rules engines for advanced data I/O and data curation.
• Collaborate with stakeholders to translate business needs into technical knowledge representation solutions.
• Mentor junior engineers and implement tools for evaluating and monitoring solution performance.

Requirements

• Must be based in the USA.
• Minimum 8 years of experience as a software engineer or data scientist (6 years with a Master's degree).
• Expertise in Graph query languages such as SPARQL, Cypher, or Gremlin and associated Graph Databases.
• Proficiency in Python and SQL.
• Experience with AWS cloud resources (S3, EC2, ECS, Lambda) and Docker or other container services.
• Experience specifying and creating APIs and microservices.

Nice to have

• Degree in Computer Science or hard sciences.
• Practical experience with Generative AI solutions.

Culture & Benefits

• Opportunity to play a key strategic role in the company's AI transformation and healthcare leadership.
• Collaborative environment focused on applying cutting-edge knowledge representation techniques.
• Commitment to a productive, professional, and harassment-free working environment.
• Equal employment opportunity (EEO) employer.