Senior Data & AI Engineer and Backend Engineer with 5+ years of expertise building production-scale systems, cloud-native data platforms, and secure APIs/services. Proven track record of delivering measurable business impact through intelligent automation and data-driven solutions.
- 🚀 Architected ETL infrastructure with Apache Airflow & BigQuery to handle massive daily data workloads
- 🤖 Developed LLM-powered systems with GPT-4 & RAG delivering high-accuracy document parsing and major manual effort reductions
- 📈 Built ML recommendation engines that noticeably increased customer engagement and conversions
- ☁️ Led cloud migrations to GCP, ensuring high availability and reliability for large user communities
- 🔒 Active bug bounty hunter delivering security findings for Fortune 500 organizations
- ⚡ Optimized databases with advanced indexing strategies to achieve significant query performance gains
💻 Backend & Software Engineering
- Languages: Python (Advanced), TypeScript/Node.js, R, Bash, PowerShell
- Backend Frameworks: Django, FastAPI, Flask, Node.js (Express), gRPC services
- System Design: RESTful & GraphQL APIs, microservices, event-driven architecture, caching strategies
- Databases: PostgreSQL, MongoDB, MySQL, Redis, Oracle EBS (schema design, query optimization)
- Quality & Delivery: Git, automated testing (Pytest, unit/integration), CI/CD, code reviews
🤖 AI & Machine Learning
- LLM Integration: GPT-4 API, Prompt Engineering, RAG (Retrieval-Augmented Generation)
- ML Frameworks: Scikit-learn, TensorFlow, Feature Engineering, Model Deployment
- ML Applications: Recommendation Systems, Predictive Analytics, Anomaly Detection
- NLP: Document Parsing, Text Classification, Named Entity Recognition
📊 Data Engineering & Analytics
- ETL Pipelines: Apache Airflow, Data Validation, Quality Frameworks
- Data Warehousing: BigQuery, Snowflake, Data Modeling
- Streaming: Kafka, Real-time Processing, Event-Driven Architecture
- Analytics: Statistical Analysis, Predictive Modeling, Business Intelligence
☁️ Cloud & Infrastructure
- GCP: BigQuery, Cloud Run, GCS, Compute Engine, IAM, Cloud Functions
- AWS: EC2, S3, RDS, Lambda, CloudWatch
- Containers: Docker, Kubernetes, Helm, Container Registries
- CI/CD: GitHub Actions, Jenkins, Automated Deployment Pipelines
🔒 Cybersecurity & Penetration Testing
- Platforms: HackerOne, Bugcrowd (Active Bug Bounty Hunter)
- Testing: Web Application, Mobile Application, Network Penetration Testing
- Methodology: OWASP Top 10, Vulnerability Assessment, Ethical Hacking
- Tool Development: Custom offensive security tools (Python, Bash)
- Notable Findings: Fortune 500 companies across telecom, academia, retail, fintech, and social platforms
- Migrated legacy architecture into a GCP-native data mesh powering analytics for large architectural content libraries
- Shipped a GPT-4 + RAG document intelligence stack achieving high BoQ extraction accuracy and drastically reducing manual entry
- Embedded recommendation APIs that lifted buyer engagement and conversions through personalized suggestions
- Built Airflow + BigQuery pipelines handling high-volume streaming analytics for thousands of artists
- Automated multi-platform ingestion (Spotify, Apple Music, Amazon) with secure headless auth workflows
- Delivered Flask/React analytics surfaces backed by scalable Cloud Run deployments with automated reliability guardrails
- Created AI-assisted pricing engine that optimizes thousands of ticket listings in real time
- Hardened PostgreSQL + AWS RDS layer with targeted query tuning for faster insights
- Industrialized delivery with GitHub Actions, dramatically shrinking release cycles
- 🤖 Building production AI platforms: RAG systems, serverless inference pipelines, and real-time ML streaming on GCP/Kafka
- 🛡️ Using AI to harden security operations: intelligent red-team tooling, automated threat intel, and AI-driven vulnerability hunting
- 🌐 Deep-diving into Web3 security — smart-contract auditing, wallet threat modeling, decentralized identity safeguards
- 🔒 Continuing offensive security research and bug bounty programs to keep skills sharp and findings impactful
I'm always interested in discussing opportunities in Data Engineering, AI/ML, Cloud Architecture, and Cybersecurity.
