Professional Overview
Applied AI Engineer building and shipping production-grade AI products end-to-end, from research and prototyping through deployment, scaling, and ongoing operations. I lead cross-functional engineering teams to deliver enterprise AI systems across NLP, speech, multimodal learning, and agentic AI, with high-impact deployments.
Experience
AI Expertise
Skills
Employment Type
Description of Responsibilities
- Designed and deployed production agentic workflow pipelines (n8n, LangGraph)
- Built voice AI agent systems using VAPI + Whisper/Groq for inbound call handling
- Developed RAG pipelines with pgvector semantic search and hybrid retrieval
- Engineered LLM evaluation frameworks for prompt regression testing
Key Achievements / KPIs
- Reduced manual ops overhead by over 70%.
- Improved document Q&A accuracy by ~40% over baseline keyword retrieval.
- Catching regressions pre-deployment and reducing production incidents
Education
Field of Study: Data Science
Areas of Expertise
AI & Machine Learning Engineers
Design, train, and ship production ML models — from data pipelines to model inference at scale. Covers supervised learning, neural networks, LLM integration, and model optimisation.
