Staff Software Engineer (hybrid)

GEICO GEICO · Insurance · Bethesda, MD +2

Staff Software Engineer to lead technical strategy and implementation of knowledge graph systems, automated content generation workflows, semantic data platforms, and intelligent content delivery solutions. This role involves architecting enterprise-scale knowledge graph platforms, building automated semantic content generation systems, developing intelligent content workflows and APIs using NLP and ML, designing real-time content personalization engines, creating data ingestion pipelines, implementing semantic search, and building internal tooling. The engineer will collaborate with product managers, data scientists, and content strategists, championing engineering excellence in semantic modeling, ontology design, graph database optimization, and AI/ML integration.

What you'd actually do

  1. Architect and design enterprise-scale knowledge graph platforms that capture and model GEICO's comprehensive insurance domain expertise, customer insights, product relationships, and market intelligence
  2. Build automated semantic content generation systems that leverage knowledge graphs to create personalized insurance content, product descriptions, educational materials, and customer communications at scale
  3. Develop intelligent content workflows and APIs that use graph traversal algorithms, natural language processing, and machine learning to automate content production, template generation, and multi-channel publishing
  4. Design real-time content personalization engines that query knowledge graphs to deliver contextually relevant messaging based on customer profiles, policy information, and behavioral patterns
  5. Create sophisticated data ingestion and enrichment pipelines that continuously build and maintain knowledge graphs from structured and unstructured data sources across the enterprise

Skills

Required

  • Proven experience designing and implementing knowledge management platforms, semantic data systems, content generation tools, or AI-driven developer platforms
  • Full-stack developer with extensive experience in modern front-end frameworks (React, TypeScript), web technologies (JavaScript, HTML, CSS/SASS), backend languages (Node.js, Python, Java), and cloud platforms (Azure, AWS, GCP)
  • Strong ability to architect distributed semantic systems and graph-based microservice architectures that handle complex data relationships and scale reliably
  • Experience with knowledge graphs, semantic technologies, and AI/ML platforms such as Neo4j, Apache Jena, TigerGraph, or similar graph databases, along with NLP frameworks and content generation models
  • Familiarity with semantic web standards (RDF, OWL, SPARQL), ontology design, knowledge representation, and automated reasoning systems
  • Deep understanding of content management ecosystems, headless CMS architectures, API-driven publishing workflows, and content delivery optimization
  • Experience with AI/ML frameworks for natural language processing, content generation (GPT, BERT, T5), recommendation systems, and knowledge extraction from unstructured data
  • Product mindset and passion for building intelligent tools that solve complex content challenges and enhance user experiences through semantic understanding
  • Excellent collaboration and communication skills with ability to explain complex semantic concepts to technical and non-technical stakeholders

What the JD emphasized

  • AI-driven semantic platforms
  • knowledge graph
  • content generation
  • semantic data platforms
  • intelligent content delivery solutions
  • knowledge-driven platforms
  • AI-powered, knowledge-driven content ecosystem
  • knowledge graph platforms
  • semantic content generation systems
  • intelligent content workflows
  • content personalization engines
  • knowledge graphs
  • knowledge graphs
  • semantic search
  • knowledge graph visualization
  • knowledge graph technologies
  • content automation frameworks
  • knowledge management platforms
  • semantic data systems
  • content generation tools
  • AI-driven developer platforms
  • distributed semantic systems
  • graph-based microservice architectures
  • knowledge graphs
  • semantic technologies
  • AI/ML platforms
  • graph databases
  • NLP frameworks
  • content generation models
  • semantic web standards
  • ontology design
  • knowledge representation
  • automated reasoning systems
  • content management ecosystems
  • headless CMS architectures
  • API-driven publishing workflows
  • content delivery optimization
  • AI/ML frameworks
  • natural language processing
  • content generation
  • recommendation systems
  • knowledge extraction
  • intelligent tools
  • complex content challenges
  • semantic understanding

Other signals

  • knowledge graph
  • content generation
  • AI-driven semantic platforms
  • NLP pipelines
  • machine learning