
Staff Software Engineer (HYBRID)
GEICO · Seattle, WA
- On site
- Full-time
- $165,000 / year
- Seattle, WA
Job highlights
- Lead technical strategy for knowledge graph and content generation.
- Build AI-driven semantic platforms for content creation.
- Collaborate with product, data, and marketing teams.
- Drive insurance business transformation with AI.
- Architect enterprise-scale knowledge graph systems.
About the role
About GEICO
At GEICO, we offer a rewarding career where your ambitions are met with endless possibilities. Every day, we honor our iconic brand by offering quality coverage to millions of customers and being there when they need us most. We thrive through relentless innovation to exceed our customers’ expectations while making a real impact for our company through our shared purpose.
When you join our company, we want you to feel valued, supported, and proud to work here. That’s why we offer The GEICO Pledge: Great Company, Great Culture, Great Rewards, and Great Careers.
About the Role
GEICO is seeking an experienced Staff Software Engineer to join our Knowledge Graph and Content Generation engineering group. This is a high-impact team focused on scaling GEICO's intelligent content creation capabilities through advanced graph-based technologies and AI-driven semantic platforms. In this role, you will lead the technical strategy and implementation of knowledge graph systems, automated content generation workflows, semantic data platforms, and intelligent content delivery solutions that empower our content, marketing, and customer experience teams.
As part of the MarTech organization, this Staff Engineer will collaborate closely with product managers, data scientists, content strategists, and marketing teams to design and deliver cutting-edge knowledge-driven platforms that enable personalized, contextually relevant content generation at enterprise scale. You'll work hands-on across the technology stack, from graph databases and semantic modeling to NLP pipelines and content delivery systems, while influencing architecture decisions and engineering best practices.
You will help drive our insurance business transformation as we transition from traditional content creation methods to an AI-powered, knowledge-driven content ecosystem that delivers exceptional customer experiences, while co-creating a culture of innovation, psychological safety, and continuous improvement.
Responsibilities
- 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.
- Build automated semantic content generation systems that leverage knowledge graphs to create personalized insurance content, product descriptions, educational materials, and customer communications at scale.
- 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.
- Design real-time content personalization engines that query knowledge graphs to deliver contextually relevant messaging based on customer profiles, policy information, and behavioral patterns.
- Create sophisticated data ingestion and enrichment pipelines that continuously build and maintain knowledge graphs from structured and unstructured data sources across the enterprise.
- Implement semantic search and content discovery platforms that understand customer intent and context through graph-based query processing and recommendation algorithms.
- Build internal dashboards and tooling for content performance monitoring, knowledge graph visualization, semantic relationship analysis, and content optimization insights.
- Lead cross-functional collaboration with product managers, data scientists, and content strategists to translate business objectives into scalable knowledge-driven technical solutions.
- Champion engineering excellence in semantic modeling, ontology design, graph database optimization, and AI/ML integration best practices.
- Mentor engineering teams on knowledge graph technologies, content automation frameworks, and distributed system design patterns for semantic platforms.
Qualifications
- 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.
- In-depth knowledge of CS data structures, algorithms, particularly graph algorithms, semantic matching, and distributed system design patterns.
- Experience with MLOps, data pipeline orchestration, and real-time semantic data processing at scale.
Experience Requirements
- 6+ years of professional software development experience building full-stack web applications, data platforms, or knowledge management systems.
- 4+ years of experience with system architecture and design, particularly in semantic data systems, graph databases, or AI-powered content platforms.
- 4+ years of experience with cloud platforms (AWS, GCP, Azure) including graph database services, ML platforms, and distributed semantic processing.
- 2+ years of hands-on experience with knowledge graphs, semantic technologies, or AI-driven content generation systems.
- Bachelor's degree in Computer Science, Data Science, Computational Linguistics, or equivalent work experience with demonstrated expertise in semantic technologies.
Key skills/competency
- Staff Software Engineer
- Knowledge Graph
- Content Generation
- Semantic Data Platforms
- AI/ML
- NLP
- Graph Databases
- System Architecture
- Full-Stack Development
- Cloud Platforms
Skills & topics
- Staff Software Engineer
- Knowledge Graph
- Content Generation
- Semantic Technologies
- AI
- Machine Learning
- Graph Databases
- System Architecture
- Full Stack Development
- Cloud Computing
- Software Engineering
- MarTech
- NLP
- Data Science
- TypeScript
- React
- Node.js
- Python
- Java
- AWS
- Azure
- GCP
- Neo4j
- TigerGraph
- Apache Jena
- RDF
- OWL
- SPARQL
How to get hired
- Tailor your resume: Highlight experience with knowledge graphs, semantic technologies, AI/ML, and full-stack development, matching keywords from the Staff Software Engineer job description.
- Showcase your portfolio: Demonstrate successful projects in system architecture, graph databases, and content generation tools on platforms like GitHub.
- Prepare for technical interviews: Brush up on data structures, algorithms (especially graph algorithms), semantic matching, and distributed systems design.
- Articulate your impact: Be ready to discuss how you've driven business transformation and enhanced user experiences through intelligent content solutions.
- Research GEICO's culture: Understand their commitment to innovation, customer service, and the GEICO Pledge (Great Company, Culture, Rewards, Careers).
Technical preparation
Behavioral questions
Frequently asked questions
- What specific graph databases are preferred for the Staff Software Engineer role at GEICO?
- While the job description mentions Neo4j, Apache Jena, and TigerGraph as examples, GEICO is open to candidates with experience in similar graph databases. Your ability to architect and implement robust graph-based systems is key.
- What is the hybrid work policy for the Staff Software Engineer position at GEICO?
- This Staff Software Engineer role is designated as hybrid, indicating a blend of remote and in-office work. Specific details on the expected in-office days and location will typically be discussed during the interview process.
- How important is experience with NLP and content generation models for this role?
- Experience with NLP frameworks and content generation models (like GPT, BERT, T5) is highly valued, as this Staff Software Engineer position is central to scaling GEICO's intelligent content creation capabilities.
- What kind of career growth can I expect as a Staff Software Engineer at GEICO?
- GEICO emphasizes 'Great Careers' with personalized development programs, industry-leading training, certification assistance, and mentorship. As a Staff Engineer, you'll have opportunities to lead technical strategy and mentor teams, driving significant impact.
- Does GEICO offer sponsorship for this Staff Software Engineer position?
- At this time, GEICO will not sponsor a new applicant for employment authorization for this position.
- What are the key technologies involved in the Staff Software Engineer role at GEICO?
- The role involves a broad range of technologies including knowledge graphs, semantic technologies, AI/ML, NLP, full-stack development (React, TypeScript, Node.js, Python, Java), and cloud platforms (Azure, AWS, GCP).
- How does GEICO approach innovation and transformation in its tech teams?
- GEICO thrives on 'relentless innovation' and is transforming its content creation methods towards an AI-powered, knowledge-driven ecosystem. The MarTech organization, where this role sits, is at the forefront of this change.
- What is the typical interview process for a Staff Software Engineer at GEICO?
- While not explicitly detailed, expect a process that likely includes resume screening, technical interviews assessing your knowledge graph, system design, and coding skills, and behavioral interviews focusing on collaboration and leadership.