Logan Kitchen

Building an LLM-based data validation platform within a microservice architecture, from model evaluation through production deployment and on-call support.

• Designed and implemented an LLM-based data validation system to identify exceptions and reduce manual audit overhead; delivered 40 custom exception validators ahead of schedule (target: end of year, completed in August).
• Built an evaluation harness to benchmark LLM candidates across accuracy, latency, and token cost; guided model selection and optimized system prompts for token efficiency while meeting all required accuracy metrics.
• Worked on a 5-microservice architecture with Python/FastAPI back-end services, Next.js front end, PostgreSQL database with Alembic migrations, and Pydantic validation; integrated with numerous third-party external microservices.
• Deployed via Jenkins → AWS Lambda → Kubernetes → Spinnaker/Helm pipeline; managed environment configuration and secrets through AWS Secrets Manager.
• Served as on-call engineer for production deployments; triaged and resolved live production issues and monitored cross-service logs via OpenDashboard.
• Partnered closely with a Subject Matter Expert team for requirements gathering, production verification, and deployment planning, translating business needs directly into technical specifications.

Independent full-stack and AI engineering contracting for small businesses.

• Full-stack website design and redesign for a materials manufacturing company, equipment retailer, and other small businesses; set up hosting on AWS and GCP.
• Built an on-site offline LLM using the DeepSeek open-source model to support project management and development tasks without exposing data to external AI services.
• Created an agentic AI team using the Anthropic API with a product owner agent and multiple developer agents, coordinating development efforts for significantly increased delivery efficiency.

Modernized a legacy DOD application and established secure development and delivery environments.

• Rebuilt a severely outdated application using React/Next.js, migrated Python 2 to 3, and restructured the entire MongoDB schema; resulting application met DOD security requirements and was significantly faster and more maintainable with a fraction of the original code.
• Designed and stood up a robust dev environment from scratch with separate dev, test, and production modes using Node.js, Python venv, pnpm, dependency scripts, and a full dummy database for end-to-end testing before delivery.
• Completed DOD security certifications and built the application to DoD specifications to operate with classified data in secure facilities; able to obtain clearances if needed.
• Created a direct installation script and a Docker image that passed DOD screening and were transmitted over secure channels.
• Mentored two team members who struggled with HTTPS between front and back end; both became independently capable of connecting to and modifying Python API endpoints.
• Selected to test a secure internal LLM AI agent due to the sensitivity of data handled; could not use public LLM services such as ChatGPT.

Led consolidation and integration of healthcare data systems and modernized internal IT and cloud infrastructure.

• Consolidated data from 5 separate manual systems into a single SQL database and Java API connected to a company-wide EHR and departmental Angular/Node.js SPAs; drastically reduced team workload and improved billing accuracy across the company.
• Integrated the consolidated data platform with the state crisis call center and Regional Behavioral Health Authority APIs over HTTPS, enabling real-time automatic updates between systems and freeing healthcare providers to spend more time with patients.
• Replaced post-it-note IT tracking with Jira and Confluence; automated ticket creation for IT calls and emails, generated reports for the CEO, and demonstrated a 50% increase in IT staff productivity in the first month, with continued gains.
• Migrated applications from individual MS Server VMs in GCP to a small set of headless Linux servers, reducing annual cloud costs by thousands of dollars and improving system performance by orders of magnitude.

Developed enterprise-scale Java back-end systems for criminal justice data processing.

• Developed a code generation template for criminal justice data translation classes that automated ~90% of each new class; completed a backlog originally estimated at one year of work in 3 months.
• Worked on enterprise-scale Java back-end systems with complex database design, REST API standards, and Java threading and concurrency to handle large-scale data processing across federal, state, and local systems.
• Completed certifications in CJIS Security, Cybersecurity Fundamentals, Java Security, and Records Management.

Developed web applications while leading agile process improvements and stakeholder requirements gathering.

• Streamlined scrum processes and shifted team culture toward shared ownership; improved sprint completion rates from ~50% to 90–100%.
• Led requirements gathering and demo sessions with department directors to build a unified web application integrating scheduling, travel, training, and medical systems; stakeholders consistently praised the outcome.