Build and scale data pipelines and partner integrations for an end-of-life open-source software dataset. Responsibilities include improving data quality, designing configurable risk-scoring models, integrating Kafka and data lakes, automating package generation and publishing, implementing monitoring and CI/CD, and documenting systems. The role also involves technical design, code reviews, mentoring, and collaboration with product and partner-facing teams.
Senior Software Engineer - IntegrationsAbout the job
HeroDevs is hiring a Senior Software Engineer for our Evergreen team. HeroDevs keeps critical open-source software secure long after it reaches end of life. The Evergreen team owns EOLDS, our end-of-life dataset, which internal teams and integration partners rely on to understand which open-source software has reached end of life, the risk that carries, and how to remediate it. We also build the systems that turn that data into packages our partners can consume, and we need those systems to produce packages at scale when a partner needs them.
Position SummaryWe're looking for a Senior Software Engineer to help take EOLDS to its next stage. You'll help build the pipelines that let us generate and publish large numbers of packages for partners on demand. This is a high-ownership role. You'll make design decisions, set patterns for the team, and work closely with partner-facing teams to understand what partners need from the data.
Responsibilities- Improve EOLDS data quality through validation, deduplication, provenance tracking, and automated checks that catch regressions before they reach partners
- Investigate and document how our current risk heuristics work, including their inputs, assumptions, and edge cases
- Design and build a multi-model risk scoring framework that supports different risk profiles for remediation, including CVE-centric models alongside our existing heuristics
- Build weighted, configurable scoring so risk profiles can be tuned per partner or use case, with clear explanations of how a score was produced
- Integrate EOLDS with Kafka and our data lake, including event schemas, producers and consumers, backfills, and consistency between systems
- Build automated pipelines that can generate, version, and publish large numbers of packages for partners on demand, reliably and reproducibly
- Add monitoring and data quality metrics so problems with the dataset, scoring, or package delivery surface quickly
- Work with product and partner-facing teams to translate partner requirements into data and scoring changes
- Write services and tooling in TypeScript/Node.js, with automated testing and CI/CD
- Review code and designs, mentor other engineers, and help raise the team's engineering bar
- Write clear documentation for the dataset, scoring models, and pipelines you build
- Work to automate package requests from our partners
- 5+ years of professional software engineering experience, with significant time spent building data-intensive systems or data pipelines in production
- Proficiency in TypeScript/JavaScript (Node.js)
- Experience with event streaming platforms such as Kafka, and with data lakes or data warehouses
- Strong SQL and data modeling skills
- Experience designing data validation and data quality checks for datasets other teams or customers depend on
- Comfort reasoning about scoring, ranking, or heuristic systems, such as weighted models or risk scores, and explaining their tradeoffs
- Experience building build, release, or publishing automation, including CI/CD pipelines
- The ability to dig into an unfamiliar system, figure out how it works, and write it down so others can understand it
- Strong written communication and the ability to drive technical decisions in a distributed team
- Bachelor's degree in Computer Science or a related field, or equivalent practical experience
- Experience with git-based software development (preferably on GitHub)
- Familiarity with vulnerability data and scoring, such as CVEs, CVSS, EPSS, CISA KEV, OSV, or GitHub Security Advisories
- Experience with package ecosystems and their publishing workflows, such as npm, Maven, PyPI, RPM, or Debian packaging
- Experience with schema registries and serialization formats such as Avro or Protobuf
- Experience with lakehouse table formats such as Apache Iceberg, Delta Lake, or Parquet-based storage
- Background in software supply chain security, including SBOMs, artifact signing, or provenance (e.g., Sigstore, SLSA)
- Experience working with enterprise partners on data delivery or integrations
- Experience mentoring engineers or acting as a technical lead
- Interest in open-source software and long-term maintenance of critical software
- Experience with Temporal Cloud or similar orchestration solutions
- Experience with OpenSearch and/or ElasticSearch
- Experience with OTEL/opentelemetry and Grafana
- Experience with Argo UI
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