Jesse Griffith

<p>Architected end-to-end agentic workflows using Claude’s reasoning capabilities to automate complex, multi-step customer success pipelines.<br>
Developed a Support Agent using Retrieval-Augmented Generation (RAG), which resolved 65% of Tier-1 tickets and reduced manual intervention.<br>
Integrated LangChain and Claude’s proprietary APIs into a Next.js frontend, which optimized internal data retrieval and cut response times for the sales team by 50%.<br>
Fine-tuned open-source models (such as Llama 3) to better handle niche industry terminology, resulting in a 22% increase in sentiment analysis accuracy for specialized client datasets.</p>

<p>Architected end-to-end agentic workflows using Claude’s reasoning capabilities to automate complex, multi-step customer success pipelines.</p><p> - Developed an autonomous Support Agent utilizing Retrieval-Augmented Generation (RAG); this system successfully resolved 65% of Tier-1 support tickets, significantly reducing the need for manual human intervention.</p><p> - Integrated LangChain and Claude’s proprietary APIs into a Next.js frontend, which optimized internal data retrieval and cut response times for the sales team by 50%.</p><p> - Fine-tuned open-source models (such as Llama 3) to better handle niche industry terminology, resulting in a 22% increase in sentiment analysis accuracy for specialized client datasets.</p>

<p>Led the migration of legacy monolithic architectures into high-performance, cloud-native microservices.<br>
Orchestrated migration from on-premises servers to AWS Lambda and Kubernetes, slashing annual infrastructure overhead costs by $150,000.<br>
Built high-concurrency backend services using Go and Rust, improving API response times by 40% under peak loads.<br>
Implemented automated CI/CD pipelines that reduced deployment-related downtime to near zero.</p>

<p>Led the migration of legacy monolithic architectures into high-performance, cloud-native microservices.</p><p> - Orchestrated a total migration from on-premise servers to AWS Lambda and Kubernetes, which slashed annual infrastructure overhead costs by $150,000.</p><p> - Built high-concurrency backend services using Go and Rust, improving API response times by 40% under peak loads.</p><p> - Implemented automated CI/CD pipelines that reduced deployment-related downtime to near zero.</p>

<p>Designed complex data visualization dashboards to translate massive datasets into actionable executive insights.<br>
Built a real-time telemetry dashboard using React and D3.js for Fortune 500 clients, handling over 1M data points per second.<br>
Optimized frontend state management, resulting in a 30% increase in rendering performance on low-powered devices.<br>
Developed ETL pipelines to clean and structure messy behavioral data, improving the reliability of monthly BI reports.</p>

<p>Designed complex data visualization dashboards to translate massive datasets into actionable executive insights.</p><p> - Built a real-time telemetry dashboard using React and D3.js for Fortune 500 clients, handling over 1M data points per second.</p><p> - Optimized frontend state management, resulting in a 30% increase in rendering performance on low-powered devices.</p><p> - Developed ETL pipelines to clean and structure messy behavioral data, improving the reliability of monthly BI reports.</p>

<p>Served as an early-hire engineer responsible for building and scaling the MVP of a social fitness application.<br>
Built the initial web platform from scratch using the MERN stack, helping the company scale from 0 to 50,000 active users in 18 months.<br>
Refactored the database schema (MongoDB), which reduced query latency by 45% during high-traffic marketing events.<br>
Implemented a responsive UI that maintained a 4.8-star user satisfaction rating across mobile and desktop.</p>

<p>Served as an early-hire engineer responsible for building and scaling the MVP of a social fitness application.</p><p> - Built the initial web platform from scratch using the MERN stack, helping the company scale from 0 to 50,000 active users in 18 months.</p><p> - Refactored the database schema (MongoDB), which reduced query latency by 45% during high-traffic marketing events.</p><p> - Implemented a responsive UI that maintained a 4.8-star user satisfaction rating across mobile and desktop.</p>