Senior, Staff Software Engineer – Parser Team

Job Description

Take ownership of the parser framework by identifying abstraction-worthy patterns, designing fundamental primitives for parser authors, optimizing performance in critical areas, and elevating the team's reliability and testability standards. Make critical design decisions involving schema mapping, normalization tradeoffs, handling ambiguous or corrupted data, and determining when to generalize versus specialize or evolve the framework. Spearhead impactful parser integrations end-to-end, demonstrating framework-level thinking and setting best-practice examples for the team. Collaborate with detection, data, and integration teams to ensure that parsed data meets the needs of downstream applications and passes validation. Provide mentorship to junior engineers through design discussions and code reviews, fostering their growth into independent contributors. Accelerate your parser development with LLM-based coding assistants, AI-driven test generation, and automated code review tools. Leverage LLMs to analyze unfamiliar log samples, propose initial parsing rules, and expedite new integrations while applying human judgment to address AI errors. Automate routine parser tasks, such as regression testing, schema diffing, and sample ingestion, to free up time for tackling complex challenges. Assist the team in integrating AI tools into their daily parser workflows and measuring efficiency improvements.

Qualifications

1. Bachelor's or Master's degree in Computer Science, Engineering, or a related field. 2. 5+ years of software engineering experience with a focus on data parsing, integration, or log processing. 3. Strong proficiency in Python, Java, Ruby, or C++. 4. Familiarity with common log formats and data structures (JSON, XML, CSV, syslog, key-value, unstructured text). 5. Strong command of regular expressions and other pattern-matching techniques. 6. Understanding of data normalization, schema design, and transformation principles. 7. Experience integrating with APIs, web services, and streaming data sources. 8. Ability to use AI tools (Copilot, Cursor, Claude, ChatGPT) to accelerate engineering workflows. 9. Working understanding of cybersecurity concepts and data security tools. 10. Strong problem-solving skills and clear communication with engineers and non-technical stakeholders.