Open to opportunities

Jordan Daniel

@jordandaniel

Message

Senior AI/ML engineer specializing in production-grade LLM, RAG, and MLOps solutions.

United States

Message

What I'm looking for

I seek senior roles building production LLM and MLOps platforms in collaborative, security-conscious teams where I can drive architecture, reliability, and measurable business impact.

I am a Senior AI Engineer with 9+ years architecting and scaling enterprise-grade machine learning and Generative AI platforms, focused on LLMs, RAG architectures, prompt engineering, and vector search. I build cloud-native AI systems with strong MLOps/LLMOps foundations, observability, automated quality gates, and secure APIs in Python.

I have led healthcare and retail AI initiatives, designing PHI-aware Generative AI systems, production LLM microservices, retrieval pipelines, and automated CI/CD and monitoring solutions. I partner closely with product, compliance, security, and engineering teams to deliver reliable, auditable AI services that improve accuracy, reduce hallucinations, and support business objectives.

Experience

Work history, roles, and key accomplishments

Lead AI Engineer

Cigna Healthcare

Feb 2019 - Nov 2025 (6 years 9 months)

Designed and deployed healthcare-focused Generative AI and RAG systems that improved answer accuracy and reduced hallucinations, built PHI-aware LLM microservices and MLOps pipelines to ensure auditability and operational reliability.

LLM RAG Vector Search Prompt Engineering Python fastAPI MLOps CI CD Model Monitoring

Senior Machine Learning Engineer

Walmart Global Tech

Aug 2017 - Dec 2018 (1 year 4 months)

Implemented large-scale ML and NLP solutions for ecommerce—product classification, attribute extraction, and semantic search—improving catalog quality and discoverability while delivering production ML microservices and MLOps pipelines.

NLP Embeddings Semantic Search Python fastAPI MLOps CI CD Data Pipelines

Software Engineer

FIS

Aug 2015 - Jul 2017 (1 year 11 months)

Developed ML models and real-time inference services for fintech use cases including transaction classification and anomaly detection, and implemented MLOps pipelines and data ingestion for large-scale financial datasets.