From full-stack development to production AI—building, operating, and shipping real-world workloads across cloud platforms and applied AI.
I'm an AI Engineer & IT Professional focused on building and operating production systems. My background spans full-stack and backend engineering, cloud platforms, and applied ML/MLOps, with an emphasis on reliable deployments, observability, and responsible AI practices.
I care about the full lifecycle: design, implementation, rollout, monitoring, evaluation, and iteration. I prefer clear tradeoffs over hype and aim to build systems that behave well under real constraints: cost, latency, reliability, security, and maintainability.
I share how I approach architecture, code quality, and production debugging—focusing on safe changes, measured outcomes, and better operational readiness.
LLMs, Generative AI, RAG systems, Vector databases, MLOps, Prompt engineering, Model evaluation, System design, Scaling AI workloads, Production ML pipelines, CI/CD for AI, Model governance, Ethical AI practices.
Build reliable AI and cloud systems and share practical patterns—focused on reliability, observability, and responsible usage.
Help more engineers and teams build AI systems that are useful, safe, and maintainable—without sacrificing engineering fundamentals.
Technical leadership for AI and platform work: architecture decisions, implementation reviews, rollout planning, and operational readiness for production systems.
Built and operated ML systems and pipelines. Focus areas included MLOps foundations, evaluation workflows, and platform tooling for repeatable deployments.
Led backend & ML work across system design, deployments, CI/CD, and platform reliability. Built tooling to improve release speed and operational consistency.
Backend & full-stack development with an emphasis on API design, performance, and maintainability.
Explore my full tech stack, how I build and operate systems, or get in touch with feedback or questions.