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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in building and maintaining web drivers and test agents, with a strong focus on anomaly detection, capacity forecasting, and integrating AI tools into engineering workflows. Proficient in Python and TypeScript, with hands-on experience in deploying solutions using Kubernetes and CI pipelines.
Highest-signal resume keywords
Python ProgrammingMachine Learning FrameworksAnomaly DetectionKubernetes DeploymentEnd-to-End Project Delivery
ATS Keywords
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Hard Skills
PythonTypeScriptAnomaly DetectionTime-Series ForecastingOutlier DetectionMachine LearningEnd-to-End TestingData IngestionRoot-Cause AnalysisModel Evaluation
Tools & Technologies
DockerGitCI PipelinesKubernetesHelmGrafanaPrometheusVictoriaMetricsOpenTelemetryBrowser Automation
Industry Keywords
Data ScienceStatisticsObservabilityAI IntegrationModel Context Protocol
Tech Stack
Tools & technologiesDockerGrafanaKerasKubernetesPrometheusPythonPyTorchScikit-LearnTensorflowTypeScript
About the role
Key responsibilities & impact- Build and maintain web drivers and test agents for end-to-end scenarios against the k0rdent web UI and APIs
- Convert test findings into clear, reproducible defects for owning teams
- Make test runs safe for live systems by preserving sessions and context, cleaning up changes, and requiring review before writing to shared systems such as Jira
- Evaluate language models for the test harness using repeatable scenarios and measured results
- Develop anomaly detection and capacity forecasting models using metrics and logs from k0rdent environments
- Measure detection quality against labeled failure sets and real workloads, and improve models
- Build LLM-assisted root-cause analysis that generates likely causes and suggested fixes from raw alerts
- Work with the observability team to deliver confirmed findings into alerting and Grafana dashboards
- Integrate AI tools into daily engineering workflows, including new builds and pull requests
- Collaborate with KOF, QA and k0rdent engineering teams to identify AI and data science improvements
- Package and deploy solutions to Kubernetes using container images, Helm charts and CI pipelines
Requirements
What you’ll need- Bachelor's or Master's degree in Computer Science, Data Science, Statistics or a related field, or equivalent practical experience
- 0 to 2 years of professional software development experience, including internships
- Strong Python, including practical experience with at least one ML framework (scikit-learn, PyTorch, TensorFlow or Keras)
- Working proficiency in TypeScript
- Hands-on experience with at least one of: anomaly detection, time-series forecasting, or outlier detection
- Experience building LLM applications, such as agentic loops, tool use, prompt design or model evaluation
- Working knowledge of Docker, Git and CI pipelines
- Demonstrated ability to ship end-to-end projects, from data ingestion through a working interface or report
- Experience with Kubernetes and Helm preferred
- Experience with observability stacks such as Prometheus, VictoriaMetrics, OpenTelemetry and Grafana preferred
- Experience with browser automation or end-to-end test frameworks preferred
- Familiarity with the Model Context Protocol (MCP), LLM gateways or multi-model routing preferred
- Experience with graph-based or topology-aware root-cause analysis preferred
Benefits
Comp & perks- Direct mentorship from the Office of the CTO and senior R&D engineers
- Ownership of production tools that other engineering teams rely on
- Work on AI infrastructure: agentic testing, applied ML on live platform telemetry, and Kubernetes-native platforms
- Competitive salary and benefits package
- Flexible working schedule
- Remote / or hybrid work environment
- Competitive compensation package
- Open-source innovation
- Collaborative, growth-oriented work environment