A track record of building innovative solutions, leading cross-functional teams, and delivering scalable products across diverse technologies and domains.
DD
Full-Stack Lead Engineer & Founder (Cloud & AI Systems)
Responsible for the technical roadmap and architecture of a portfolio of SaaS and AI platforms for clients, translating business needs into a prioritized roadmap of over 5 initiatives.
Led multi-cloud DevOps delivery of microservices handling over 1,000 concurrent requests across more than 3 client missions in parallel: Kubernetes/Docker, Terraform, and CI/CD on AWS, Azure, and GCP.
Integrated AI coding tools (Claude, Claude Code) into daily development (precise prompts, generated code review, self-correction and automated testing steps), improving result reliability by 30% and reducing manual QA effort by 40%.
Defined engineering standards (code review, testing, data flows) on production systems.
Designed and built a scalable data ingestion pipeline in Python, Django, and Procrastinate (PostgreSQL-backed task queue) that automates the reliable processing of complex professional election records (PVs) from raw documents to structured, queryable data. Adding new feature on innovative platform (benefits.artikle.io)
Shipped new features on the benefits.artikle.io platform, including a human-only live support chat with two-way Slack threading, so support staff can reply from Slack and users see replies in-app.
Optimized data retrieval from the pipelines to surface company benefits and PV data to end users, including information that was previously not exposed, using scheduled cron jobs and LLM-assisted extraction.
Corrected and improved ingested data quality, and optimized existing features including API-based data extraction.
Developing a 100% human live support chat in Django, with bidirectional Slack threads (signed webhook, kill switch, AWS Secrets Manager), first deployed to staging.
Technologies
PythonDjangoLLMAWS ServicesData ScrapingAPIsAsynchronous Cron Jobs
Developed Node.js/.NET Core back-ends exposing optimized GraphQL and REST APIs on PostgreSQL and MongoDB, with multi-level caching and clear data models.
Responsible for architecture, performance, and scalability choices on over 4 client projects, independently from specification to deployment.
Created reusable cloud-deployable UI components and Docker workflow modules, reducing delivery times by 20%.
Architected a real-time game-state synchronization engine utilizing WebSockets and Redis, ensuring sub-millisecond latency for live chess matches and multiplayer interactions.
Designed and deployed a containerized microservices architecture using Docker and Kubernetes on AWS, implementing auto-scaling policies to handle high-concurrency traffic spikes during live events.
Integrated Stripe and local payment methods with secure event-driven webhooks.
Architected a conversational AI REST service for bookings, support, and contextual requests, automating over 70% of common inquiries across multiple channels.
Built validation pipelines based on schema-constrained LLM outputs for reliable API responses; designed a semantic search engine and real-time recommendation system to improve conversion.
Technologies
StripeLLMREST APIWebhooksSemantic SearchRecommendation System
Modernized legacy REST APIs into a unified access-controlled GraphQL layer (SSO, OAuth2, MFA), raising integration test coverage to over 80% (Jest, Cypress) for a SaaS platform streaming to over 10,000 devices (Shell, HP, Carrefour, Nissan).
Containerization and multi-cloud CI/CD (Kubernetes, Docker, Terraform) on AWS and Azure, reducing deployment times by 30%.
Queue-based transcoding pipeline (Redis, BullMQ) processing over 5,000 jobs per day.
Event-driven fleet monitoring system feeding a centralized ELK pipeline: automatic anomaly detection and MTTR reduced by 50%.
Frontend SPA rebuild with React, TypeScript, Vite, and Tailwind CSS on Cloudflare Workers, reducing bundle size by 45%.
Defined code quality standards, code reviews, and mentored over 3 junior developers.