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
