Kendis - Streamlining Agile at Scale ยท 4 hours ago
AI Engineer
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Responsibilities
AI Model Development: Design, train, and deploy machine learning models for predicting Agile team performance, sprint velocity, and project risks.
Data Analytics: Leverage Agile data (e.g., flow metrics, cumulative flow diagrams) to extract actionable insights and trends.
Integration with Kendis Platform: Build AI/ML-based analytics modules that integrate seamlessly with Kendis, Jira, and Azure DevOps.
Natural Language Processing (NLP): Develop NLP-based features such as automated status reporting, sentiment analysis from team comments, and task prioritization.
Predictive Analytics: Implement models to forecast delivery timelines, bottlenecks, and team productivity metrics.
Visualization Tools: Work with the UI/UX team to create intuitive dashboards and visualizations of AI-generated insights.
Performance Monitoring: Monitor AI systems to ensure high accuracy and reliability in real-world applications.
Collaboration: Collaborate with product managers and engineers to align AI features with business goals and user needs.
Qualification
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Required
3+ years in AI/ML engineering or data science roles, with a focus on analytics or enterprise solutions.
Proficient in Python, R, or Java, with expertise in AI/ML libraries like TensorFlow, PyTorch, or Scikit-learn.
Strong skills in data preprocessing, cleaning, and feature engineering for large datasets.
In-depth knowledge of machine learning algorithms (e.g., regression, clustering, neural networks) and their application.
Experience in Natural Language Processing for text analysis and sentiment extraction.
Hands-on experience with visualization tools like Power BI, Tableau, or Matplotlib.
Familiarity with cloud-based AI/ML platforms (e.g., AWS SageMaker, Azure AI, Google AI).
Understanding of Agile methodologies, metrics, and frameworks such as SAFe, Scrum, or LeSS.
Ability to work with cross-functional teams, including product, development, and customer success teams.
Preferred
Experience in building AI tools for project management or productivity platforms.
Familiarity with Agile tools such as Jira or Azure DevOps.
Certifications in AI/ML or data science (e.g., Google AI Engineer, AWS Certified ML Specialist).
Understanding of Agile analytics like flow efficiency, cumulative flow diagrams, or velocity charts.
Experience with time-series analysis or predictive modeling in project management contexts.
Company
Kendis - Streamlining Agile at Scale
Kendis is a tool for the practicalities of scaling agile, crafted to simplify the complexities of frameworks and methodologies like SAFe, Scrum at Scale, and Tribe model (aka Spotify model).
Funding
Current Stage
Growth StageCompany data provided by crunchbase