Principal Software Engineer Search Systems

LexisNexis Risk Solutions is a leading organization in advanced information and decision support for science and healthcare. They are seeking a Principal Software Engineer with extensive search experience to design and implement complex search and retrieval systems, mentor team members, and collaborate with various teams to deliver effective technical solutions.

Responsibilities:

• Leading architectural design and ensure technical consistency
• Helping lead our shared search platform – expanding content search, improving relevance via vector and lexical search techniques
• Building world-class search systems to enhance users’ search experience
• Automating processes to assist other teams
• Collaborating on new ideas to optimize systems and engineering workflows
• Building relationships with other engineering teams to identify and solve their pain points
• Working across the stack, from development to infrastructure
• Designing and developing scalable data processing workflows and microservices using Spark, Spark Streaming, and Airflow
• Writing clean, modular, and testable code in Python, Java, or Scala, aligned with coding standards and architecture guidelines
• Lead implementation of system components that span multiple services and modules
• Diagnose and resolve complex technical issues across distributed systems and data workflows
• Leading design discussions, code reviews, and architecture sessions to ensure software quality and maintainability
• Developing and maintain data models to support analytical and operational use cases
• Collaborate with cross-functional stakeholders to translate product requirements into reliable engineering solutions

Requirements:

• Current expertise with Lucene, Elasticsearch, Solr, or any other search engine, and have industry experience with Semantic Search
• Proven track record building search systems at scale
• Proficiency in batch processing technologies, including Spark, Spark Streaming, Airflow
• Expertise in at least one of Java, Python, Scala
• Deep understanding of distributed system design, data modeling, and performance tuning
• Experience with test-driven development and CI/CD practices
• Ability to independently drive technical outcomes from problem definition to deployment
• Familiarity with Agile, Kanban, or other iterative development methodologies
• Familiarity with vector/embedding-based search, KNN algorithms
• Exposure to graph-based data models or knowledge graph architecture
• Experience building internal platforms or developer-facing data tooling
• Knowledge of observability best practices for data systems (e.g., metrics, logs, alerts)