About Me
I am a senior AI engineer and full-stack software engineer with a strong focus on building end-to-end products that combine machine learning, retrieval, and modern web technologies.
I have experience taking products from zero to production, including architecture, implementation, deployment, and measurable performance improvements. My work has included recommendation systems, chatbot APIs, and retrieval-augmented generation pipelines.
I work comfortably across the stack, with hands-on experience in React, TypeScript, Next.js, FastAPI, Django, and REST APIs. I also have deep experience with Python-based ML workflows, model training, semantic search, and LLM evaluation.
My background includes building systems around PostgreSQL, Neo4j, MongoDB, Redis, Elasticsearch, Kafka, and AWS infrastructure. I care about scalable architecture, clean engineering practices, and shipping reliable products.
I have led technical work in startup environments, collaborated with founders and teams, and owned code quality through reviews and iterative delivery. I enjoy solving complex product and infrastructure problems with practical engineering decisions.
I am open to opportunities where I can contribute as a senior individual contributor or technical leader in AI, machine learning, and full-stack product engineering.
Skills
PythonSQLAWSJavaScriptReactDockerTypeScriptMachine LearningPostgreSQLKafkaMongoDBETLRedisREST APIsNoSQLPerformance OptimizationPyTorchTensorFlowElasticsearchNext.jsDjangoDeep LearningLLMAPI DesignfastAPINatural Language ProcessingData MiningFlaskOAuthEvent Driven ArchitectureKibanaNginxCachingDomain Driven DesignFunctional ProgrammingRecommendation SystemsModel EvaluationJWTNeo4jXGBoostSemantic SearchBERTCaddyRAG
Tech Stack & Tools
Data Stores
Libraries
Monitoring
Experience
Took the recommendation platform from zero to production as decoupled microservices on AWS using Docker. Built a hybrid recommendation and retrieval engine over PostgreSQL and Neo4j, synchronized through Kafka. Shipped chatbot and recommendation APIs in FastAPI with Redis caching, led code reviews for a team of 4, and fine-tuned an open-source LLM with a vector RAG pipeline.
Built an MLflow-tracked ETL pipeline over noisy multi-source data, surfaced trends with XGBoost and embedding-based semantic search for 20 franchises, and ran KPI monitoring on the ELK stack while optimizing MongoDB queries for analytics.
Pretrained a BERT model for domain-specific semantic search and embeddings. Trained and deployed models on AWS with Redis caching and collaborated with the CEO on research and new AI product direction.
Built a payment gateway with Next.js and a Django REST backend, integrating Stripe and crypto payments. Resolved N+1 query issues, optimized the client with Redux and memoization, and tested with Jest and Selenium.
Built and maintained scalable full-stack web applications using React and Django. Designed responsive UIs, robust RESTful APIs, secure authentication and authorization flows, and improved database performance, caching, and third-party integrations.
Education
Doctoral of Philosophy (PhD), Artificial Intelligence
Doctoral studies in Artificial Intelligence, withdrawn.
Master of Science (M.S.), Data Mining (C.S)
Graduate study in data mining and computer science.
Bachelor of Science (B.S.), Computer Science
Undergraduate degree in computer science.
High School Diploma, Mathematic
High school diploma in mathematics.
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