Building
Production AI
Systems
Full-stack engineer specializing in production AI systems. Architecting scalable infrastructure, optimizing for performance and cost, and delivering systems that serve real users at scale.
Production AI Systems
Real products serving real users, with measurable business impact
Visura
Knowledge operations system processing 10,000+ documents with 94%+ accuracy. Reduced processing costs by 95% through intelligent architecture and optimization, generating $15K+ in revenue from a single project.
VectorMail
RAG-based email intelligence platform delivering sub-200ms semantic search across live email streams. Serving 1000+ indexed emails with 99.9% uptime, reducing search time by 80%.
RepoDocs
Automated code documentation system processing 200+ repositories and 100K+ LOC. Reduced onboarding time by 75% with 92% relevance accuracy, serving engineering teams at scale.
Tech Stack
Technologies
& Tools
Frontend
Backend & Databases
AI/ML
Infrastructure
Architecture
Tools & Practices
About
Expertise
& Impact
System Architecture
Designing scalable, production-grade systems from the ground up. Multi-tenant SaaS architecture with isolated data, auto-scaling infrastructure for production workloads, and cost-optimized deployments reducing spend by 95%.
AI/ML Production
Productionizing LLMs, RAG systems, and vector databases at scale. RAG pipelines processing 10,000+ documents with 94%+ accuracy, vector database optimization for sub-200ms queries, and LLM orchestration with GPT-4 and multi-provider fallbacks.
Performance & Optimization
Delivering measurable business impact through technical optimization. Reduced processing costs from $5.00 to $0.05 per document (95% reduction), sub-200ms query latency for semantic search at scale, and 99.9% uptime across production systems.
Full-Stack Ownership
End-to-end product development from architecture to deployment. 600+ production commits in 2025, shipping consistently. Independent product ownership: design, build, deploy, maintain across TypeScript, Next.js, Python, PostgreSQL, Redis, AWS, and Vercel.
I'm an AI-focused full-stack engineer building production systems that stay live under real usage. Over the past three years, I've taken products from concept to production, supporting real users, processing large volumes of data, and delivering measurable outcomes, like generating $15K+ revenue from a single project and reducing operational costs by 95%.
My strength is designing AI-driven software that holds up in practice, systems that combine retrieval pipelines, vector storage, model orchestration, and application logic into something reliable and maintainable. I've worked across the stack to ship fast, keep latency low (sub-200ms), and maintain accuracy under real workloads (94%+), while balancing cost, performance, and operational constraints.
I'm seeking full-time engineering roles at startups building serious AI products, where ownership and execution matter. I ramp quickly, operate independently, and contribute consistently, reflected in 600+ production commits tied directly to shipped features. I aim to build software that teams rely on every day, that generates measurable business value.
Professional Journey
AI Full-Stack Developer | Product Builder
Independent Product Development
Led development and ongoing operation of multiple production AI products used by active users. Scope of work included system design, feature delivery, reliability, and iteration based on live usage across independently run SaaS applications. Handled engineering across backend services, data stores, AI pipelines, and deployment infrastructure. Regularly addressed performance issues, production bugs, scaling constraints, and integration requirements involving authentication, payments, and third-party APIs. Worked in fast iteration cycles, releasing improvements continuously while keeping systems stable in production. Sustained long-term delivery pace with, focused on maintaining and improving systems that remain active and in use.