Senior Software Engineer – Semantic Layer and AI Interfaces

Nucleus Security•Remote, FL

2d•$135,000 - $165,000•Remote

About The Position

Are you looking for more in life than just building another web app? Does upending cyber security resonate with you? We're a rapidly expanding cybersecurity company revolutionizing vulnerability management for organizations of all sizes. For our customers, vulnerability management has always been a game of catch-up, with limited asset coverage and manual processes. Nucleus' primary mission is to create a fast, scalable platform that not only addresses these challenges but also makes vulnerability management simple, fun, and effortless. Currently, we're looking for a passionate Senior Software Engineer to join our growing team of engineers.

Requirements

Strong background in data analytics, data science, and/or data warehousing.
Deep expertise in SQL, including performance optimization and complex query design.
Proficiency in Python or similar language for data processing and AI integration.
Experience working in a test-driven environment and writing unit and integration tests
Proven ability in technical troubleshooting.
Capable of working independently as well as collaboratively with teams across different time zones.

Nice To Haves

Experience working with vulnerability scanning technologies on any part of the tech stack (e.g., SCA, SAST, DAST, IAST, VM Scanning, Container, etc.)
Experience with column store databases and columnar data, especially using SingleStore/MEMSQL
Experience integrating AI/LLM-driven features with data platform.
Familiarity with Agile/Scrum methodologies in a professional setting.
Experience maintaining applications on Linux platforms in cloud environments.
Experience with modern versions of PHP, and the Zend and Laminas Frameworks

Responsibilities

Own the end-to-end lifecycle of AI-driven features—from prototyping and experimentation to production deployment and customer delivery
Design, build, and evolve our semantic data layer to enable scalable, high-quality AI and analytics use cases
Collaborate with engineering, product, and data teams to translate ambiguous requirements into robust technical solutions
Diagnose, triage, and resolve production issues quickly, ensuring reliability and continuous improvement of deployed systems
Improve key components of the application to enable data scalability.