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I am a results-driven AI/ML Engineer and full-stack technologist with over 10 years of experience spanning agentic AI systems, enterprise-scale data platforms, and production machine learning solutions across healthcare, legal, ad-tech, and cloud operations. I have architected and delivered end-to-end intelligent applications, led cross-functional engineering teams, and built multi-agent orchestration systems that transform complex infrastructure into intuitive, user-facing products. I bring a deep passion for translating cutting-edge AI research into robust, scalable systems and a proven track record of driving measurable technical and cultural impact across every engagement I have led. I pride myself on mentoring and building high-performing teams; I have guided engineers on agentic AI patterns, LLMOps standards, and responsible AI guardrails, while partnering with product stakeholders to translate complex infrastructure requirements into clear technical deliverables. I excel at fostering collaboration across cloud architects, security, and domain experts to ship reliable, auditable AI-driven solutions that scale in production.…I am a results-driven AI/ML Engineer and full-stack technologist with over 10 years of experience spanning agentic AI systems, enterprise-scale data platforms, and production machine learning solutions across healthcare, legal, ad-tech, and cloud operations. I have architected and delivered end-to-end intelligent applications, led cross-functional engineering teams, and built multi-agent orchestration systems that transform complex infrastructure into intuitive, user-facing products. I bring a deep passion for translating cutting-edge AI research into robust, scalable systems and a proven track record of driving measurable technical and cultural impact across every engagement I have led. I pride myself on mentoring and building high-performing teams; I have guided engineers on agentic AI patterns, LLMOps standards, and responsible AI guardrails, while partnering with product stakeholders to translate complex infrastructure requirements into clear technical deliverables. I excel at fostering collaboration across cloud architects, security, and domain experts to ship reliable, auditable AI-driven solutions that scale in production.

Michael Raymond

Data Scientist, AI Engineer, Full Stack Developer, +2

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I am a results-driven AI/ML Engineer and full-stack technologist with over 10 years of experience spanning agentic AI systems, enterprise-scale data platforms, and production machine learning solutions across healthcare, legal, ad-tech, and cloud operations. I have architected and delivered end-to-end intelligent applications, led cross-functional engineering teams, and built multi-agent orchestration systems that transform complex infrastructure into intuitive, user-facing products. I bring a deep passion for translating cutting-edge AI research into robust, scalable systems and a proven track record of driving measurable technical and cultural impact across every engagement I have led. I pride myself on mentoring and building high-performing teams; I have guided engineers on agentic AI patterns, LLMOps standards, and responsible AI guardrails, while partnering with product stakeholders to translate complex infrastructure requirements into clear technical deliverables. I excel at fostering collaboration across cloud architects, security, and domain experts to ship reliable, auditable AI-driven solutions that scale in production.…I am a results-driven AI/ML Engineer and full-stack technologist with over 10 years of experience spanning agentic AI systems, enterprise-scale data platforms, and production machine learning solutions across healthcare, legal, ad-tech, and cloud operations. I have architected and delivered end-to-end intelligent applications, led cross-functional engineering teams, and built multi-agent orchestration systems that transform complex infrastructure into intuitive, user-facing products. I bring a deep passion for translating cutting-edge AI research into robust, scalable systems and a proven track record of driving measurable technical and cultural impact across every engagement I have led. I pride myself on mentoring and building high-performing teams; I have guided engineers on agentic AI patterns, LLMOps standards, and responsible AI guardrails, while partnering with product stakeholders to translate complex infrastructure requirements into clear technical deliverables. I excel at fostering collaboration across cloud architects, security, and domain experts to ship reliable, auditable AI-driven solutions that scale in production.

Available to hire

I am a results-driven AI/ML Engineer and full-stack technologist with over 10 years of experience spanning agentic AI systems, enterprise-scale data platforms, and production machine learning solutions across healthcare, legal, ad-tech, and cloud operations. I have architected and delivered end-to-end intelligent applications, led cross-functional engineering teams, and built multi-agent orchestration systems that transform complex infrastructure into intuitive, user-facing products. I bring a deep passion for translating cutting-edge AI research into robust, scalable systems and a proven track record of driving measurable technical and cultural impact across every engagement I have led.

I pride myself on mentoring and building high-performing teams; I have guided engineers on agentic AI patterns, LLMOps standards, and responsible AI guardrails, while partnering with product stakeholders to translate complex infrastructure requirements into clear technical deliverables. I excel at fostering collaboration across cloud architects, security, and domain experts to ship reliable, auditable AI-driven solutions that scale in production.

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Work Experience

Senior AI/ML Engineer at Deloitte

September 1, 2023 - May 1, 2026

Architected the Cloud Ops Copilot for UHS, a production multi-agent system on LangGraph that lets network engineers query Azure infrastructure in natural language, replacing tedious portal navigation. Designed a supervisor-agent orchestration pattern with LangChain tool-calling and function-calling schemas, routing intents to specialized sub-agents for topology queries, resource inventory, and incident triage. Integrated Azure OpenAI GPT-4 as the primary LLM, enforcing structured outputs via Pydantic and JSON schema to ensure deterministic, auditable responses. Built multi-CSP network path validation workflows with AutoGen-style parallel execution to speed incident response. Implemented human-in-the-loop triggers for critical decisions. Deployed as a Python FastAPI service, containerized with Docker and hosted on Azure Container Apps for scalable, region-aware delivery. Established LLMOps observability with LangSmith traces and Arize Phoenix dashboards. Crafted prompt lifecycle governa

Senior Data Scientist at Thomson Reuters

April 1, 2020 - August 1, 2023

Led end-to-end ML model development for CoCounsel's legal AI platform, from feature engineering to production deployment and monitoring. Trained supervised classification and regression models in PyTorch to automate tax document categorization and risk scoring, improving accuracy over legacy baselines. Built robust feature engineering pipelines with PySpark and Delta Lake, extracting structured signals from unstructured legal and financial documents. Orchestrated model training and nightly batch inference with Airflow to meet SLA requirements for tax advisory dashboards. Implemented SHAP/LIME interpretability to explain predictions and satisfy governance. Conducted A/B testing and statistical hypothesis testing, tracked experiments with MLflow, and maintained a model registry. Monitored data drift and performance with custom evaluation pipelines and Datadog alerts, triggering retraining when needed. Collaborated with domain experts to align models with practitioner workflows and mentor

Senior Data Engineer at WPP Media - Choreograph

March 1, 2018 - March 1, 2020

Developed backend services for Open Intelligence, Choreograph's AI-powered ad-tech platform, building Python REST APIs and microservices that connect location, keyword, interest, and content signals for advertiser activation. Engineered high-throughput data ingestion with Kafka and PySpark, streaming signals into Snowflake with schema validation and lineage tracking. Architected Airflow-powered ETL pipelines processing terabytes of data daily for planning, activation, and measurement products. Integrated ML scoring models into production via FastAPI endpoints for real-time audience segmentation. Containerized components with Docker and deployed to AWS EKS, using Terraform IaC for reproducible environments. Implemented Great Expectations for data quality across ingested datasets and built Grafana dashboards with Prometheus metrics for proactive SLA monitoring.

Data Engineer at Centene

July 1, 2016 - February 1, 2018

Ingested and standardized large-scale healthcare data spanning claims, eligibility, member enrollment, provider, pharmacy, and care-management domains into a centralized warehouse, enforcing HIPAA-compliant data masking and PII controls. Built SQL-based ETL pipelines to transform raw EDI claims into analytics-ready datasets with schema validation and data quality checks. Supported data governance by implementing lineage tracking and audit trail documentation for HIPAA compliance and full data lifecycle traceability. Collaborated with clinical and operations teams to translate healthcare data requirements into structured pipeline deliverables supporting utilization reporting and care-management analytics.