Skills

Building production LLM applications: prompt engineering for structured outputs, Batch API cost optimization, context assembly pipelines, and safety validation for LLM-generated code.

Building RAG systems with Qdrant: embedding pipelines, semantic chunking, multi-stage retrieval, context assembly, and source-attributed responses.

Building production backends with FastAPI — 50+ endpoint APIs, Pydantic validation, modular router architecture, Redis caching, and security-audited endpoints.

Expert-level Python developer with 5 years of experience across backend development, data science, machine learning, and bioinformatics.

Experienced JavaScript developer proficient in frontend frameworks and backend integration. Used across full-stack applications from React websites to WordPress plugin development.

Java developer with experience in Android development, test-driven development, and object-oriented design. Applied Java to build mobile applications with persistent storage and comprehensive testing.

C# developer with experience in object-oriented programming, completing intermediate and beginner Udemy certifications covering OOP principles and application development.

PHP developer with experience in WordPress plugin development and database integration.

Experience in object-oriented game developement using advanced OOP concepts including abstraction, inheritance, and polymorphism.

Experience with C programming for low-level systems and security applications. Implemented cryptographic algorithms and explored cyber security concepts like SQL injection prevention, SYN Flooding, and Buffer Overflow attacks.

Strong foundation in object-oriented design principles with 6 years of experience across Java, Python, and Ruby. Applied OOP patterns in game development, Android applications, and backend systems.

Experienced technical writier with formal university coursework in Technical Communication. Published author of 3 IEEE peer-reviewed papers and creator of comprehensive project documentation exceeding 30 pages.

Applied Agile/Scrum methodologies on team projects, managing sprints, user stories, and iterative development cycles.

Full-stack web developer experience with modern frontend frameworks and backend integration. Built applications using React and traditional HTML/CSS/JS with various backend technologies.

Formal project management training from university coursework combined with hands-on experience leading development teams. Applied PM skills as team lead on Android application development.

Data scientist with experience in the complete analytics pipeline: EDA, feature engineering, model training, and result interpretation.

Experienced database developer skilled in relational database design, query optimization, and secure data access. Achieved 75% query runtime improvement through B+ tree indexing.

Strong foundation in Bioinformatics with experience implementing core algorithms for genomic analysis. Built custom implementations of pattern matching and multiple sequence alignment algorithms in Python.

Machine learning developer with experience in supervised learning, neural networks, and healthcare analytics. Co-authored 3 IEEE publications applying ML to Long COVID prediction.

Defending against various cyber attacks like SQL injection, buffer overflow attacks and SYN flooding, and performing encryption and decryption.

Formal HCI coursework combined with practical application in prototype development. Applied user-centered design methodology including heuristic evaluations and user testing.

Experience with distributed systems through blockchain implementation, including peer discovery, consensus protocols, and network synchronization using Python sockets.

Graph database development with Neo4j: indexing 10,000+ functions with caller-callee relationships, Cypher queries for call tree traversal, complexity analysis, and structural code intelligence.

Experience with Flask for building backend APIs with database integration, authentication, and comprehensive testing.

Skilled in creating data visualizations with Matplotlib and Seaborn for exploratory analysis, model evaluation, and result presentation.

Experienced with NumPy for numerical computing, matrix operations, and scientific calculations. Foundation for machine learning implementations and data processing.

Proficient with pandas for data manipulation, cleaning, and analysis. Applied across multiple data science projects for EDA, feature engineering, and data preprocessing.

Experience with PyTorch for building and training neural networks, including custom model architectures and training pipelines.

Experienced with scikit-learn for training, evaluating, and tuning machine learning models. Applied to classification, regression, and feature selection tasks.

Experience with TensorFlow and Keras for building and training convolutional neural networks. Applied to image classification achieving 84% accuracy on CIFAR-10 benchmark.