1. Business-First Scope
Define the decision, owner, and success metric before model work begins.
10+ years delivering AI and data science programs
Founder & Applied AI Principal at Byteflows
Advisor to NYU on applied AI
AI Strategy & Delivery
Andi Shehu, PhD
LLM & AI Systems Architect
Principal Applied AI Specialist
I design and deliver AI systems that are reliable in production and aligned to business goals.
X LinkedIn ashehu@byteflows.com
New York, NY
PhD in Physics (Quantum Information)
Sectors: Healthcare, AdTech, Finance, Academia
Specialties: LLM systems, evaluation, delivery
Selected Work
- NYU | Applied AI Enablement Design and build an end-to-end AI research hub for discovery, synthesis, and workflow support.
- NYU | Research Adoption Train researchers to adopt AI in lab workflows and provide one-on-one advisory support across science and social science teams.
- NYU | Program Delivery Lead a focused applied AI team and support grant strategy, technical writing, and AI team design.
- Healthcare Build predictive models for Star Ratings and patient churn to support operational planning and patient-focused decisions.
- AdTech Deliver audience modeling and campaign measurement systems at Microsoft and DeepIntent, with production-grade pipelines.
- Cross-Industry Advise organizations on AI strategy, implementation, and governance.
- Operating Standard Apply scientific rigor to model quality, reliability, and risk.
Operating Principles
2. Reliable System Design
Use clear architecture, retrieval, and control layers to improve output quality and reduce failure modes.
3. Evaluation and Governance
Establish testing, monitoring, and guardrails before launch.
Experience
Applied AI Systems Consultant
Designed AI pipelines for research automation, enterprise search, and assistant products.
Senior Research Data Scientist, DeepIntent
Built audience modeling and campaign measurement systems using Python, Spark, and AWS.
Senior Research Data Scientist, Microsoft
Designed segmentation and predictive modeling frameworks and partnered with engineering to ship ML and NLP pipelines.
Founder & Applied AI Principal, Byteflows Dynamics
Led end-to-end AI engagements from problem framing through deployment for startup and enterprise clients.
Technical Stack
Focused on GenAI system design first, then reliable data, model, and deployment operations.
LLM and Agent Systems
LangChain, LangGraph, LlamaIndex, MCP, tool calling, workflow orchestration
Model Ecosystem
OpenAI, Anthropic, Hugging Face, open-source models (Llama, Mistral, Qwen, Gemma)
Retrieval and Search
RAG pipelines, vector stores, Weaviate, Chroma, hybrid retrieval
Evaluation and Guardrails
Evals, tracing, observability, reliability testing, safety controls
Infrastructure and HPC
GPU-enabled pipelines, HPC/distributed compute workflows, Docker, FastAPI
Languages, Data, and Cloud
Python, R, SQL, PySpark, PyTorch, scikit-learn, AWS, Azure
Education
PhD, Physics (Quantum Information Theory) - CUNY Graduate Center, New York, NY, 2015
MS, Mathematics - Hunter College, New York, NY, 2010
From The Margin
"In strong AI work, the model is only part of the answer. The rest is context, judgment, and care."