Distinguished Technical Expertise

• 15+ years of software engineering experience with demonstrated progression to senior technical roles
• Deep expertise in distributed systems architecture at massive scale (billions of events/day, petabyte-scale data)
• Proven track record architecting AI/ML systems in production environments, including experience with:
  • Large Language Models (LLMs) and generative AI applications
  • Retrieval-Augmented Generation (RAG) architectures and vector search systems
  • Machine learning model deployment, monitoring, and MLOps practices
  • Real-time inference systems and online learning
• Expert knowledge of graph databases and graph algorithms (Neo4j, TigerGraph, or similar) including:
  • Graph data modeling and schema design
  • Complex graph queries and traversals (Cypher, Gremlin, or similar)
  • Graph algorithms for community detection, centrality, path finding
  • Large-scale graph processing and analytics
• Master-level proficiency in Python and modern ML/AI frameworks (TensorFlow, PyTorch, LangChain, LangGraph)
• Deep understanding of data engineering including:
  • Streaming data architectures (Kafka, Flink, Pulsar)
  • Large-scale data storage (ClickHouse, Snowflake, BigQuery, data lakes)
  • ETL/ELT pipeline design and optimization
  • Real-time and batch processing paradigms

AI/ML for Security Specialization

• Hands-on experience building AI-powered security solutions such as:
  • Behavioral analytics and user/entity behavior analytics (UEBA)
  • Anomaly detection using unsupervised and semi-supervised learning
  • Threat classification and automated triage systems
  • LLM-based security assistants and conversational interfaces
  • Graph neural networks for security relationship modeling
• Expertise in vector databases (Pinecone, Weaviate, Chroma, Milvus, pgvector) and their application to:
  • Semantic search over security data
  • Threat intelligence matching and similarity analysis
  • Security knowledge base construction
• Deep understanding of embedding models and semantic representation of security concepts
  • Experience with prompt engineering, fine-tuning, and LLMOps best practices