The Position

Our team builds the technology that tells the world what's inside its software. Our engines scan source code and binaries to detect open-source components, generate Software Bills of Materials (SBOM), and surface vulnerabilities and license risks across the software supply chain.

We are looking for an early-career Software Engineer AI-native, someone who treats AI coding assistants as a core part of their workflow and is curious about how machine learning can make component detection and vulnerability analysis smarter. You'll join a team that ships fast, reviews rigorously, and expects AI tools to amplify (not replace) sound engineering judgment.

What You Will Be Doing

Design, implement, and maintain features for our SBOM generation and SCA scanning engines
Use agentic AI coding tools daily (Claude, Copilot, Cursor, or similar) to speed up development, testing, and review: prompting, verifying, and iterating with judgment
Stay current on emerging AI coding tech and help the team adopt what actually improves developer experience
Build and improve data pipelines that ingest package registry, vulnerability, and license data at scale
Write clean, well-tested code and participate in code reviews with senior engineers
Investigate detection accuracy issues and continuously improve scan quality
Collaborate with QA, product, and other engineering teams across the SCA platform

What We Need from You

Bachelor's degree in Computer Science, Software Engineering, Information Technology or related field
1-3+ years of professional experience
Solid foundation in data structures, algorithms, and at least one systems or backend language (Python, Go, C/C++, Java, or Rust)
Hands-on experience using AI coding tools (Claude Code, Copilot, Cursor, ChatGPT, or similar) on actual projects
Fundamentals in machine learning and data processing: understanding of core ML concepts (classification, embeddings, evaluation metrics) and comfort working with data: parsing, transforming, and analyzing structured/unstructured datasets
Familiarity with Git and collaborative development workflows
Ability to read and communicate in English (written and verbal)
Curiosity, ownership, and a habit of verifying; especially the output of AI tools

It Would Be Nice If You Had

Rust programming experience: personal projects, coursework, or open-source contributions all count
Exposure to LLM APIs, prompt engineering, RAG, or building AI-assisted features
Experience with CI/CD pipelines, Docker, or Linux environments
Contributions to open-source projects

Software Engineer (AI-native)