Led POC’s to expand AppD’s/Splunk’s footprint at existing clients, and to generate net new busines at potential clients. Architected and deployed observability solutions tailored for AI/ML workloads, ensuring robust monitoring and performance optimization. Responsible for a book of 12 clients with 1.2m+ ARR, all of which have expanded their spend. Identified client pain points and structured solutions to sell and embed AppDynamics/Splunk. Collaborated with data science teams to design and manage machine learning pipelines in containerized environments using Kubernetes and Docker. Developed extensions, structured creative solutions to ensure fullstack application visibility. Advocated for the adoption of cutting-edge AI tools and frameworks, conducting technical workshops to demonstrate business value. Utilized containers and orchestration platforms to instrument containerized architectures with AppDynamics/Splunk. Led training initiatives (office hours calls, training sessions and initiatives,troubleshooting sessions,etc.) to clients.

Responsible for enterprise level Dynatrace configuration, application triage, support, plugin implementation, and troubleshooting. Designed and implemented MLOps pipelines for healthcare AI applications, leveraging AWS and Azure environments for scalability. Led proofs of concept for AI-driven solutions, including NLP and predictive analytics. Optimized data pipelines to improve ML training efficiency and model serving. Led POC’s for application groups to adopt Dynatrace. Led implementation in Azure and AWS. Determined workarounds for fullstack visibility into unsupported technology platforms with limited license availability. Developed training on the utility of Dynatrace and its many use cases. Established full scale alerting and anomaly detection, management zones, and integration with other platforms.

Application performance consultant for Walgreens, Kaiser Permanente, Enterprise and Northwestern Mutual Insurance, responsible for implementing, managing, and keeping hundreds of applications (200+ at Northwestern Mutual) healthy. Integrated advanced machine learning models with Dynatrace to enhance anomaly detection and root cause analysis. Instantiated and configured Dynatrace in a variety of cloud-based applications in AWS, Azure, GCP,and multiple other PaaS platforms in every conceivable technology suite. Structured the implementation, configuration, and deployment of the OneAgent across all of the supported (and some unsupported) technologies. Implemented CI/CD workflows to streamline AI/ML model deployment and infrastructure management. Developed custom plugins in Python for ML-based insights and operational efficiency. Trained users on Dynatrace software and application performance topics, identifying problems and other application issues, and best practices for approaching application triage. Performed application triage for issues associated with applications across the full stack (front andback end). Developed plugins and other software in both Python and Json in order to extend the capability of Dynatrace across the full application delivery chain. Presented extensively on the capabilities of Dynatrace to audiences ranging from technical/engineering roles all the way to the business-facing side.

Implemented various statistical tools, programming in R and Python, and software packages to perform predictive analysis on large data sets. Spearheaded machine learning projects, including natural language processing (NLP) and predictive modeling, leveraging TensorFlow and Python. Designed statistical models and classifiers to solve complex business challenges, such as regression analysis and pattern recognition. Utilized a variety of machine learning/probabilistic classifiers, including: regression analysis, support vector machines, Naïve Bayes, and regression trees (random forests, etc.). Spearheaded a natural language processing machine learning project involving optimization,Google’s Doc2Vec software, and Python to develop a package capable of performing sentiment analysis.

Conducted an overhaul on U of M’s previous network; organized and managed layout of computer networks and updates to previous systems. Developed a method to map network connectivity that saved U of M hours of rote labor.