
11 - 50 employees
Founded 2021
đ€ Artificial Intelligence
âïž SaaS
đ€ B2B
đ„ Funding within the last year
đ° $12M Series A - Rwazi on 2025-07
Artificial Intelligence âą SaaS âą B2B
Rwazi is a B2B SaaS company that provides real-time consumer data and AI-driven insights to help global brands grow revenue, protect market share, and enter new markets. Its Lumora platform automates data collection, predictive modeling, and goal-driven recommendations, while Sena is a conversational AI copilot that gives instant, role-specific answers and execution guidance. Rwazi turns consumer behavior signals into actionable strategies for targeting, pricing, product and go-to-market decisions.
đ February 28
đ Anywhere in the World
â° Full Time
đĄ Mid-level
đ Senior
đ”ïž Threat Intelligence Specialist
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11 - 50 employees
Founded 2021
đ€ Artificial Intelligence
âïž SaaS
đ€ B2B
đ„ Funding within the last year
đ° $12M Series A - Rwazi on 2025-07
Artificial Intelligence âą SaaS âą B2B
Rwazi is a B2B SaaS company that provides real-time consumer data and AI-driven insights to help global brands grow revenue, protect market share, and enter new markets. Its Lumora platform automates data collection, predictive modeling, and goal-driven recommendations, while Sena is a conversational AI copilot that gives instant, role-specific answers and execution guidance. Rwazi turns consumer behavior signals into actionable strategies for targeting, pricing, product and go-to-market decisions.
âą Evaluating decision outputs for logical integrity and sound reasoning âą Identifying patterns of judgment failure or inconsistency âą Designing structured feedback loops to improve AI reasoning âą Training and refining AI judgment frameworks âą Defining measurable standards for decision quality âą Review system outputs for logical coherence and reasoning rigor âą Assess signal interpretation accuracy âą Identify tradeoff miscalculations or flawed inference pathways âą Document recurring reasoning gaps âą Create structured examples to refine reasoning performance âą Develop edge-case libraries for training robustness âą Formalize evaluation rubrics for decision quality âą Collaborate with R&D to improve reasoning architecture âą Define measurable criteria for decision-grade output âą Track improvements in reasoning consistency âą Monitor drift in output quality over time âą Establish acceptance thresholds for release âą Identify systemic reasoning weaknesses âą Surface blind spots in signal modeling âą Propose structured adjustments to logic layers âą Escalate structural flaws early âą Partner with Product to align quality with roadmap goals âą Collaborate with R&D on advanced reasoning improvements âą Provide structured feedback to Engineering when system behavior deviates
âą Strong analytical and logical reasoning ability âą Experience evaluating AI systems, decision frameworks, or complex models âą Comfort dissecting multi-step reasoning chains âą Ability to formalize judgment criteria âą Strong written clarity and structured thinking âą Comfort working with ambiguity and edge cases
âą Flexible / Remote
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