Senior Backend Engineer | AI/ML Systems Architect | Data Engineering Specialist

Seasoned backend engineer with deep expertise in designing and implementing scalable, production-grade systems. Specialized in AI-powered applications, distributed data pipelines, and high-performance microservices architectures. Known for exceptional debugging capabilities and systematic root cause analysis that ensures system reliability and optimal performance.

• Microservices design and implementation with Django, FastAPI, and Node.js/Express
• RESTful API development with comprehensive authentication and authorization
• Real-time systems using WebSockets and event-driven architectures
• Advanced debugging and root cause analysis for complex distributed systems

• Production LLM applications with OpenAI and Anthropic Claude APIs
• Retrieval-Augmented Generation (RAG) systems with vector databases
• Prompt engineering, fine-tuning, and model optimization
• AI-powered SaaS platform development

• ETL/ELT pipeline development with Apache Airflow and PySpark
• Stream processing with Apache Kafka for real-time data workflows
• Data warehouse architecture and optimization with Snowflake
• Large-scale data transformation and analytics

• AWS cloud-native application deployment and management
• Docker containerization and orchestration
• CI/CD pipeline implementation with GitHub Actions
• Database performance tuning and optimization (PostgreSQL, MySQL, MongoDB, Redis)

• Expert-level debugging across full stack and distributed systems
• Root cause analysis methodology for production incidents
• Performance profiling and optimization
• System monitoring, logging, and observability implementation

expertise = {
    "languages": ["Python", "JavaScript/Node.js", "SQL"],
    "frameworks": ["Django", "FastAPI", "Express.js", "Flask"],
    "data_engineering": ["Apache Airflow", "PySpark", "Kafka", "Pandas", "Snowflake"],
    "databases": ["PostgreSQL", "MySQL", "MongoDB", "Redis", "Vector DBs"],
    "cloud_platforms": ["AWS (EC2, S3, Lambda, RDS, CloudWatch)"],
    "devops": ["Docker", "Git", "GitHub Actions", "Nginx"],
    "ai_ml": ["OpenAI API", "Claude API", "LangChain", "Vector Embeddings"]
}

• End-to-end backend system design and implementation
• Microservices migration and modernization
• API design and development with comprehensive documentation
• Performance optimization and scalability improvements

• Custom LLM application development and integration
• RAG system implementation with semantic search
• AI agent development and workflow automation
• Model evaluation and prompt optimization

• Data pipeline architecture and implementation
• Real-time streaming data processing
• Data warehouse design and ETL development
• Workflow orchestration and job scheduling

• Production incident investigation and resolution
• System performance analysis and tuning
• Code review and refactoring for maintainability
• Technical debt reduction strategies

• Architecture reviews and recommendations
• Technology stack evaluation and selection
• Best practices implementation
• Team mentoring and knowledge transfer

My systematic debugging methodology combines:

• Structured root cause analysis using the "5 Whys" and fault tree analysis
• Comprehensive logging and monitoring implementation
• Distributed tracing for microservices debugging
• Performance profiling and bottleneck identification
• Hypothesis-driven troubleshooting for complex system issues

This approach has consistently reduced mean time to resolution (MTTR) and improved system reliability across production environments.

I'm interested in challenging roles and projects involving:

• Complex distributed systems architecture
• AI/ML platform development and scaling
• High-volume data processing systems
• System reliability engineering and optimization

Available for senior backend engineering positions, technical leadership roles, and specialized consulting engagements.

Committed to writing clean, problem solving, debugging, maintainable code and building systems that scale.