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Infrastructure Solutions Engineer specializing in scaling AI integrations, cloud architecture, and secure enterprise deployments.

Core Technical Focus

AI Engineering
Hybrid RAG pipelines, semantic chunking, evaluation loops (Ragas), LLM orchestration frameworks.
Infrastructure & Cloud
Enterprise architecture, hybrid networks, IAM security boundaries, resilient API middleware.

Featured AI Solutions Engineering Projects

Enterprise RAG Pipeline with Automated Eval Loop

Faithfulness: >99% | Context Precision: 0.94

Designed and deployed a highly modular, production-grade retrieval pipeline engineered to handle complex corporate documentation without hallucination regressions.

Architecture Stack: Python, FastAPI, pgvector, Cohere Rerank.
Key Achievement: Built a custom automated evaluation suite running on every commit to measure semantic accuracy, cutting down context retrieval window size while maximizing relevance scores.

Resilient High-Throughput Agentic Router

p95 Latency: -40% | Token Eff: +35%

Developed a stateful customer routing agent running production guardrails to completely eliminate breaking API exceptions under heavy bursts of traffic.

Architecture Stack: LangGraph, Pydantic, OpenTelemetry, Redis.
Key Achievement: Engineered a token-bucket rate limit throttler with exponential backoff and structured output enforcement, maximizing cache hits to optimize API usage overhead.