Kwesi Boahene

Managed 50+ associates across 2 shifts, implementing automated reporting workflows to monitor real-time throughput data and flag performance deviations without manual intervention Leveraged AI-assisted analytics tools to model labor demand and optimize staffing allocations, driving a 40% improvement in team productivity Built and deployed custom KPI dashboards integrating automated data pipelines to surface operation bottlenecks and accelerate data-driven decision cycles

Area Manager I, Operations at Amazon (2026-01 – Present)

• Managed 50+ associates across 2 shifts, implementing automated reporting workflows to monitor real-time throughput data and flag performance deviations without manual intervention
• Leveraged AI-assisted analytics tools to model labor demand and optimize staffing allocations, driving a 40% improvement in team productivity
• Built and deployed custom KPI dashboards integrating automated data pipelines to surface operation bottlenecks and accelerate data-driven decision cycles
• Partnered with Safety, HR and Quality to identify process inefficiencies, resolve operational challenges and maintain compliance

AI Trainer (via Contractor) at OpenAI (2025-09 – Present)

• Conduct failure mode analysis on multimodal AI models across text, vision, and reasoning tasks, identifying systematic errors and edge cases using structured evaluation rubrics
• Perform adversarial testing and prompt engineering to probe model weaknesses, policy violations, and reliability issues
• Support model improvement pipelines through systematic annotation and documentation in distributed evaluation environment

Independent AI Engineer at Freelance (2025-01 – Present)

• Designed end-to-end AI system for healthcare clients with lead generation, referral management, and automated outreach
• Built PostgreSQL database schema and Supabase functions for real-time workflow automation and data management
• Developed Python pipeline integrating SERP API and proprietary LLM models, reducing processing time from weeks to 2 hours
• Achieved 60% operational efficiency improvement through RAG implementation and agent orchestration

Data Analyst at Telus International AI (2023-07 – 2024-08)

• Optimized AI chatbot performance through A/B testing, scenario analysis, and iterative prompt refinement, reducing handling time by 28% and increasing agent satisfaction by 37%
• Conducted quantitative analysis on search engine performance data, leading to enhanced SEO optimization

B.S. in Econometrics & Quantitative Economics – University of Illinois Urbana-Champaign (2025-05)