Cognira

Data Engineer

• Compare Apache Spark and DuckDB on existing transformations to select suitable transformations for migration
• Implement DuckDB versions of selected transformations with automated equivalence tests against Spark versions
• Develop and test a way to run DuckDB transformations on Databricks, including compute type, dependencies, and data access
• Modify pipeline orchestration so each step declares whether it runs on Spark or DuckDB
• Create a command to run DuckDB transformations locally with sample data or cloud storage data
• Ensure one code version for each transformation runs locally and on Databricks without changes
• Build a science module that groups products into likely complements and substitutes and assembles product hierarchies from product descriptions
• Develop a prototype AI debugging agent, its read-only toolset, and an evaluation framework for identifying root causes of forecast differences
• Benchmark deep learning forecasting models against production models and analyze when they improve promotional demand forecasting performance

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Data Engineer Intern, Data Science Intern

QA Engineer

• Develop an AI-powered test management tool covering requirements review, test cases, executions, results, traceability, and risk-based regression prioritization.
• Design and validate requirements and design documentation with the QA team.
• Migrate existing test cases and integrate with automated tests and Cognira Test Hub.
• Build an AI-based hybrid API and UI performance testing framework using k6/xk6, TypeScript, Docker, Go, CI/CD, Grafana, and HTML reports.
• Create environment profiles, performance scenarios, dashboards, reports, documentation, and baseline campaigns.
• Analyze authorized application logs to identify errors, anomalies, and related events.
• Reconstruct incident timelines and generate evidence-based reproduction steps and potential root causes.
• Generate investigation summaries and bug report drafts with evidence, reproduction steps, and confidence indicators.
• Build a historical incident knowledge base and classify new incidents against similar historical cases.
• Provide a CS-friendly interface or structured output for investigation results and classification suggestions.
• Evaluate accuracy, usefulness, and potential time savings; document architecture, limitations, and future improvements.

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Quality Assurance Intern, Customer Services Intern

Full-stack Engineer

• Develop a visual screen builder using Storybook components, predefined layouts, TypeScript component definitions, JSON schemas, and MCP integration
• Build interactive MCP Apps for PromoAI's Cora AI assistant, including charts, data tables, product and store pickers, alerts, calendars, and forecast visualizations
• Implement MCP Apps support in Cora's MCP server with text-based fallback responses
• Build adaptive light and dark theme styling across host AI applications
• Create automated frontend and backend tests and compatibility reports for Claude, ChatGPT, Gemini, and VS Code
• Build an intelligent test-impact selection service that identifies affected tests, explains selections, generates replay reports, and integrates with CI/CD
• Develop a full-stack application for reviewing AI-generated code, including code comments, explanations, pull-request walkthroughs, collaborative reviews, and human validation
• Deliver technical documentation and final project demonstrations

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Open roles

Data Engineer Intern, Data Science Intern

Quality Assurance Intern, Customer Services Intern

Software Engineer Intern