Hire Alfred J. - Forward Deployed Engineer

Architected a full-stack task management system from the ground up, implementing features such as Kanban interfaces, flexible status taxonomies, deduplication logic, and automated task generation workflows. Currently productizing the internally-proven solution into a market-ready SaaS product using JavaScript, Flutter and Google Cloud Platform. Conceived and Executed a complete website rebuild that achieved perfect Lighthouse performance scores (100/100) while driving a 300% conversion rate increase and 92% reduction in operational costs. Utilised modern web technologies including 11ty static site generation, serverless computing, scalable cloud infrastructure (AWS/GCP) and A/B Testing with Netlify to create a high-performance, cost-efficient solution. Built a comprehensive analytics pipeline facilitating Anomaly Detection and Insight Generation via heuristics generated from automated customer and competitor data collection via Google Analytics, Google Cloud Platform and a JavaScript backend. Implemented SEO strategies for customer acquisition not only for core terms but for adjacent trending keywords. Resulted in 106% growth in organic traffic and 164% increase in search impressions with Google Search Console and Google Trends.

* Received recognition for demonstrating the Ownership and Deliver Results Leadership Principles, highlighting my ability to own a problem to completion on time. Ranked top engineer in organization. Guided the team in shifting operational focus from queue reduction to root cause analysis. This strategic shift resulted in fewer operational issues, improved service quality and higher quality ops time for engineers. During subsequent operational weeks, I led by example by pushing solutions for all recurring issues, setting a standard for proactive problem-solving and reducing future workloads for the team by 43% averaged over ops rotation. Created automated testing services using Hydra and ECS deployed using CloudFormation for both services launched in my tenure. Prioritizing cost effectiveness by working backwards for thresholds and frequencies. Achieved 51% of cost estimate assisting other teams optimize. Developed a MVP for a Timeseries Service on AWS Sagemaker Instances. Datasets were generated, evaluated and ranked on how predictable they were inspired by “On the Predictability of Time Series” Hyndman et al. to rank relative performance in Python. Models implemented in PyTorch were selected from various fields statistics, AI and trained and best result utilized. Worked on automated region builds for services using TypeScript, CDK and Jinja templates reducing new region launch time by factor of 10.