I’m a senior AI full-stack engineer with experience at Google, Microsoft, and BIK.ai, where I build reliable, user-focused products from the first idea through production.
I’m a senior AI full-stack engineer with experience at Google, Microsoft, and BIK.ai, where I build reliable, user-focused products from the first idea through production. I enjoy working directly with customers, translating their needs into practical solutions, and delivering AI features quickly across industries including fintech, legal, real estate, e-commerce, healthcare, and logistics. My work combines modern web development, cloud platforms, large language models, RAG systems, and thoughtful evaluation practices.
TypeScript
Node.js
JavaScript
Python
Tailwind
Docker
Azure
AWS
KubernetesAmazon Web Services
GitHub
.NET
C#
PostgreSQL
ASP.NET
GraphQL
React NativeBuilt Bik.ai, an AI-powered business intelligence platform that uses LLMs, RAG, and intelligent agents to turn business data and documents into actionable insights. Developed PythonFastAPI backend services, AI workflows, retrieval pipelines, API integrations, and scalable cloud infrastructure. Focused on reliable data processing, contextual AI responses, automation, and production-ready architecture.
Architected and delivered secure, scalable AI-powered full-stack applications and cloud services using React, Next.js, TypeScript, Node.js, Python, AWS, Docker, CI/CD, and infrastructure as code. Built LLM integrations, RAG pipelines, responsive interfaces, REST APIs, third-party integrations, and automated workflows with n8n, Zapier, and Make.com. Led technical reviews, mentored engineers, and translated customer requirements into scalable delivery plans.
Built scalable full-stack web applications, APIs, and AI-enabled features for advertising and consumer platforms using React, TypeScript, Node.js, Python, REST APIs, Google Cloud, Terraform, Docker, and CI/CD. Implemented monitoring, validation, alerting, reusable components, third-party integrations, and early AI feature engineering focused on prompt and context preparation.
Built full-stack and backend services for enterprise productivity and collaboration products on Azure, serving millions of users across Microsoft 365 and related platforms. runbooks that shortened onboarding for new engineers.
Validates professional skills in implementing, deploying, and operationalizing machine learning solutions on AWS. Covers data preparation, model development, model deployment, inference, monitoring, security, scalability, and production ML workflows using AWS services such as Amazon SageMaker. Demonstrates the ability to move machine learning solutions from development into reliable, scalable production environments.
Validates professional expertise in designing, building, evaluating, productionizing, and optimizing machine learning and AI solutions on Google Cloud. Covers data preparation, model development, model evaluation, deployment, scalable inference, ML pipelines, monitoring, responsible AI, and production operations. Also demonstrates knowledge of implementing AI solutions using foundation models and modern generative AI capabilities.
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