Engineer who owns systems end to end — architecture and research through implementation, production deployment and post-production operations. Seven years in event-driven distributed systems at Walmart and NielsenIQ (1.5M transactions/day, 99.99% availability), the last three building production GenAI retrieval at IBM: hybrid dense/sparse search, agent-orchestrated MCP retrieval, and a multi-tenant customer-facing SaaS platform on IBM Cloud.
Languages: Go, Java, Python, C++, SQL
GenAI & Retrieval: Retrieval-Augmented Generation (RAG), Agent Orchestration, Model Context Protocol (MCP) servers & tools, Hybrid Dense/Sparse Retrieval (BM25, SPLADE), Cross-Encoder Re-ranking, Embedding Models, Retrieval Evaluation (Recall@k, offline eval), LLM Fine-tuning & Extended Pre-training, Synthetic Data Generation, Claude Code; Elasticsearch, OpenSearch, MilvusDB, ANN Indexing (HNSW, IVF)
Streaming & Data: Apache Kafka — Kafka Connect (source/sink connectors), exactly-once semantics, idempotent producers, consumer groups, partition & replication strategy, rebalancing, offset management, broker tuning, capacity planning; Redis Streams, Dead Letter Queues, PostgreSQL, MongoDB
Distributed Systems & Operations: Event-Driven Architecture, Microservices, Multi-Tenant SaaS, High Availability, Leader Election, API Design (gRPC, REST, GraphQL), CPU/Memory Profiling, Latency & Throughput Optimization, Load Testing, SLO/SLA Ownership, On-Call & P1 Incident Response
Cloud & Platform: IBM Cloud, Microsoft Azure, Kubernetes (Helm, HPA), Docker, IBM Z (s390x), Spring Boot, Resilience4j, CI/CD, Grafana, Prometheus, Jaeger