Job Title:  Consultant | AI / ML | Across Locations | Artificial Intelligence & Data | AI Insights & Engagement

Built an institutional memory layer serving 30+ internal users by transforming enterprise documents and
operational data into a persistent conversational knowledge system.
• Rearchitected a hybrid RAG search system into a state-machine design, achieving ∼80% reduction in cost per
query and ∼50% reduction in input tokens through architectural optimizations across 5 iterations.
• Fine-tuned Snowflake Arctic Embed v2 using hard negative mining and Matryoshka loss on domain-specific data
(EPC, solar contracts), achieving R@1 = 0.629 (+8.4% over baseline), matching Gemini-level retrieval performance.
• Built real-time Voice AI agents using Pipecat and WebRTC with streaming STT, LLM, and TTS pipelines,
implementing turn-taking, silence detection, and latency optimization for conversational context management.
• Developed a reusable LangGraph agent orchestration framework enabling Agent2Agent communication, stateful
execution, dynamic task routing, and tool integration for enterprise workflows.
• Architected a multi-agent contract intelligence platform (Supervisor, SME, Database, Asset agents) generating
structured outputs with human-in-the-loop validation, improving document processing reliability.
• Deployed Qwen-14B with LoRA adapters and 8-bit quantization on vLLM (GCP) for real-time analytics, enabling
cost-efficient inference at scale while maintaining output quality.
• Integrated MCP, REFRAG, mem0, and an LLM Wiki system to enable tool orchestration, persistent cross-session.

Preferred Qualifications

• Microsoft Certified: Power Platform Functional Consultant
• Microsoft Certified: Power Platform Developer Associate (PL-400)
• Microsoft Certified: Power Platform Solution Architect (Preferred)
• Microsoft Copilot Studio Certification (Preferred)