David Thompson

Senior Full-Stack AI Engineer with 9+ years of experience building scalable SaaS platforms, AI workflow automation systems, and cloud-native applications across healthcare and enterprise environments. Specialized in Generative AI, Voice AI agents, RAG pipelines, and multi-agent AI systems using React, Next.js, Python, FastAPI, LangChain, and AWS. Experienced delivering production-grade AI platforms focused on intelligent automation, real-time communication, and operational efficiency.

Senior AI Full Stack Engineer at Striveworks LLC (2024-04 – 2026-03)

• Led development of a HIPAA-compliant AI workflow automation platform for healthcare providers using React, Next.js, Python, FastAPI, and AWS, enabling real-time voice, text, and document-driven workflows that scaled across clinical and care-coordination teams.
• Engineered production-grade Voice AI agents using Deepgram, Whisper, ElevenLabs, and WebSocket-based streaming architectures to automate patient intake, appointment coordination, triage interactions, and follow-up workflows while reducing operational response time by 40%.
• Built low-latency RAG-based clinical automation pipelines using Amazon Bedrock, Pinecone, and FastAPI, integrating EHR context, medical knowledge sources, and intelligent retrieval systems to improve AI response relevance and increase clinical documentation completeness by approximately 30%.
• Designed and implemented autonomous multi-agent AI systems using LangChain, LangGraph, and MCP-driven tool orchestration for care-plan routing, escalation handling, task coordination, and patient communication automation, reducing manual administrative workload by over 50%.
• Engineered scalable cloud-native microservices and AI inference infrastructure on AWS using EKS, Lambda, Docker, SageMaker, and CI/CD pipelines, achieving 99.8% platform uptime while improving deployment scalability and reducing infrastructure costs through autoscaling strategies.
• Implemented secure multi-tenant healthcare architectures with RBAC, audit logging, PHI isolation, and LLM observability pipelines including hallucination detection, RAG relevance scoring, and compliance-safe monitoring to support reliable and HIPAA-aligned AI operations in production environments.

Full Stack Engineer at DeepHow (2021-03 – 2024-02)

• Built and maintained customer-facing SaaS applications using Next.js, TypeScript, GraphQL, and React, supporting more than 50K monthly users across manufacturing and industrial sectors for workforce training, operational reporting, and knowledge-capture workflows.
• Developed scalable backend services and GraphQL APIs using FastAPI, Python, and Node.js to power DeepHow's AI-driven knowledge platform, improving knowledge-transfer efficiency by approximately 30% and reducing customer support requests by 18%.
• Created and optimized cloud-native deployment infrastructure on GCP using GKE, Cloud Run, Docker, and GitHub Actions CI/CD pipelines, improving deployment reliability while reducing infrastructure costs by nearly 20%.
• Built internal analytics dashboards and reporting pipelines using Next.js and FastAPI, enabling enterprise clients to monitor workforce knowledge usage and reducing analytics turnaround time from days to hours.
• Improved application scalability and backend responsiveness through Redis caching strategies, asynchronous processing workflows, API optimization, and database performance tuning, reducing average API response times by approximately 35% across high-usage enterprise environments.
• Mentored junior engineers on TypeScript, FastAPI, Docker, and modern development best practices while collaborating with product managers and cross-functional teams to improve sprint planning efficiency and reduce post-release defects by 25%.

Backend Developer at Google (2019-03 – 2021-02)

• Expanded scalable backend services and RESTful APIs using Python, Node.js, FastAPI, and NestJS, supporting distributed internal systems and high-volume operational workflows across engineering platforms.
• Designed and optimized backend data-processing pipelines integrating PostgreSQL, MongoDB, and Redis, improving query performance and reducing average API response latency by approximately 30%.
• Built asynchronous service architectures and internal API integrations that reduced backend processing bottlenecks by 30% and refined service reliability across divided engineering applications.
• Contributed to cloud-native infrastructure deployment workflows across AWS and GCP using Docker, Kubernetes, and CI/CD automation, improving deployment consistency and reducing release turnaround times across development environments.
• Boosted backend scalability and operational efficiency through Redis caching strategies, database optimization, and service-level tuning, reducing backend latency by 25% and improving application responsiveness across internal platforms.

Frontend Developer at Google (2018-03 – 2019-02)

• Developed responsive frontend applications and reusable UI component systems using React, Angular, Next.js, and TypeScript, improving interface consistency and reducing frontend feature implementation time by 25%.
• Built interactive dashboards and integrated frontend applications with RESTful and GraphQL APIs, streamlining operational workflows and improving accessibility of engineering data across distributed teams.
• Enhanced frontend usability and application performance through component optimization, modular UI architecture, and modern frontend development practices across internal operational platforms.

Software Engineering Intern at Google (2017-06 – 2018-02)

• Improved internal web applications and React-based frontend components, improving engineering team productivity by streamlining operational workflows and reducing manual task time by an estimated 20–30%.
• Supported debugging, UI testing, API integration tasks, and frontend enhancements while collaborating with senior engineers in agile development environments.

Bachelor's of Degree in Computer Science – Texas Tech University (2014 – 2017)