Alex Duvall

• • Pioneered AI-powered LCA methodology reducing industrial coatings sustainability analysis from 9 months to 90 days through LLM/AI-powered automation, enabling $1M ARR in engineering services revenue
• • Delivered 13 Scope III emissions reports (EPDs) in record 72 days supporting $5M RFQ requirement, vs. industry standard of 9 months per report—a 10x efficiency improvement
• • Architected LLM-powered agent using OpenAI and LangChain to automate Scope III data collection from 1000 raw material suppliers, reducing manual analysis time by 85%
• • Scaled sustainability consulting practice from single client to 5 enterprise accounts through AI-enhanced delivery model, achieving 90% client retention
• • Architected comprehensive MCP (Model Context Protocol) service ecosystem with 15 custom connectors enabling autonomous LCA/EPD generation and marketing workflows, replacing manual processes with agentic AI systems

• • Architected and scaled fintech platform from 0 to 100,000 users, processing millions of daily API calls with 99.9% uptime while integrating ChatGPT for intelligent transaction insights
• • Built and led engineering team from solo founder to team of 12, increasing deployment frequency from monthly to daily while maintaining zero critical production incidents
• • Designed full-stack architecture leveraging AWS ECS, Python/Django, React Native, and FastAPI, reducing deployment cadence from 2 weeks to on-demand through automated CI/CD pipelines
• • Integrated LLM capabilities across platform for fraud detection and user support, reducing manual review time by 70% and improving customer satisfaction scores
• • Led data analytics infrastructure using Segment, Kinesis, and custom ETL pipelines, enabling real-time persona creation and reducing customer acquisition cost by 35%
• • Drove technical decisions generating 40% YoY revenue growth through strategic API partnerships, multi-asset support (stocks, crypto, points), and AI-powered recommendation engine

• • Architected and delivered custom warehouse management system from zero to production in 4 months, automating inventory tracking for 100,000 SKUs across multiple facilities
• • Built full-stack solution using React, Django, and PostgreSQL, reducing inventory reconciliation time from 8 hours daily to 30 minutes or less
• • Added real-time Excel synchronization layer using custom APIs, allowing operations team to maintain familiar spreadsheet workflows while gaining automated inventory tracking capabilities

• • Led 8-engineer team building IoT analytics platform for 10,000 remote oil & gas devices, from embedded firmware to cloud infrastructure, achieving 99.95% uptime across harsh field conditions
• • Developed embedded Linux solutions on BeagleBone and Raspberry Pi platforms using Python and C/C++, implementing edge computing algorithms that reduced cellular data usage by 75% while maintaining real-time monitoring
• • Architected hardware-software integration managing sensor protocols (Modbus, I2C, SPI), custom device drivers, and OTA firmware updates across distributed fleet with 0.1% brick rate
• • Designed fault-tolerant embedded systems with hardware watchdogs, redundant data paths, and graceful degradation, achieving 99.9% field reliability in 40°F to 140°F conditions
• • Built hybrid edge-cloud architecture processing 50GB daily sensor data, with intelligent edge filtering reducing cloud costs by 60% while maintaining millisecond-level anomaly detection

• • Architected Scala-based ETL modules processing terabyte-scale healthcare datasets using Apache Spark, reducing model training time from several days to a few hours
• • Implemented MLOps infrastructure using Terraform, Docker, and AWS, enabling rapid deployment of ML models that improved patient outcome predictions by 25%
• • Optimized Spark-based data lake architecture serving as generalized storage mechanism, reducing query times by 80%

• • Built healthcare analytics dashboard using Python/Django, Vue.js, and D3.js visualizations, serving 500 healthcare providers with real-time patient experience insights
• • Streamlined ML sentiment analysis pipeline, improving prediction accuracy while reducing inference time
• • Led front-end development implementing responsive UI/UX design that increased user engagement by 40% and reduced support tickets by 60%
• • Achieved 95% code coverage through comprehensive testing suite, reducing production bugs by 75% and deployment rollbacks

• • Led anonymized patient matching initiative processing billions of records across 100 data sources, achieving 94% match accuracy while maintaining HIPAA compliance
• • Architected data ingestion pipeline in Java processing 2TB daily, reducing processing time from 24 hours to 4 hours through parallelization and optimization
• • Developed internal analytics tools using Python/Django and pandas, enabling non-technical teams to query patient cohorts 10x faster than SQL-based approaches

• • Led data-driven validation of nuclear plant safety procedures analyzing Level 1/2/3 PRA models, identifying optimizations and supporting license extensions for US nuclear facilities
• • Developed MAAPDOSE radiation modeling software in C, replacing legacy FORTRAN system and reducing calculation time from hours to minutes
• • Modernized 100K lines of FORTRAN code to modern C with cross-platform support (Windows/Linux), improving maintainability and enabling CI/CD adoption
• • Published 3 EPRI technical reports on spent fuel pool risk assessment, establishing industry-standard methodologies adopted by US nuclear facilities

Languages

AI/ML

Cloud/Infrastructure

Web/Mobile

Data/Analytics

Embedded/IoT

Sustainability

M.S. Nuclear Engineering - Health Physics

University of Missouri

B.S. Nuclear Engineering

University of Missouri - Rolla