CONTACT INFORMATION:

Email: adt59i@r.postjobfree.com Phone: 415-***-****

Address: San Francisco, California LinkedIn: IN/daemeonreiydelle

Summary:

Highly skilled and experienced AI/GenAI Architect: hands-on AI DevSecOps & Observability Cloud Architect. 15 years of expertise in advising, designing and implementing DSS, Rule based systems, big data and AI solution infrastructures. 10+ years hybrid and cloud-based solutions. Proficient in leading projects on Azure, AWS, and Google Cloud Platform (GCP). Proven track record in productionalizing DSS, RBES on DSS, and emerging use of AI and ML models to leverage existing production DSS, RBES systems, leveraging pretrained models (Azure, GCP, ChatGPT, LLAMA, various HuggingFace OSS models, etc.) for industry automation, semiconductor fab process improvements, mining incompatible data model LIMS systems, maintenance and support RAG, etc. Strong background in data analytics, cloud architecture, and strategic planning. Excellent communication and leadership skills to collaborate effectively with cross-functional teams and stakeholders.

Visionary AI Hybrid solutions and infrastructure architect with a passion for innovation and creativity. Experience working with Fortune 500 through startups to improve private and public High Performance Computing infrastructures for ML: GenAI/LLM/DAN/RAG/Synthetic Data, Data Mesh solutions, GRC, AI Cybersecurity for autonomous, training/inference, predictive analytics, SAP ERP Supply Chain, etc.

Consulting/Advising: Big 5 experience (IBM, Accenture, Microsoft/Avanade, PWC, HCL/Axon); Beyond the PowerPoints, I have real-life, cutting-edge clients’ MLOps/ML Observability/Cloud Transformation; extensive experience finding, engaging, and delivering Practical AI, MLOps, Cybersecurity, and SRE transformations. Focus on customer-private data.

Strategy: Working with clients to develop the IT solutions that innovate for the customer. Building MLOps, DevSecOps and SRE/Observability to deliver on strategic change with a focus on 3 Sigma and Special/Common Cause COE practices.

Digital Transformations to hybrid, public, and edge cloud: support proprietary (PI, Finserve, GDPR, HIPPA) data integrations for big data lakes, ML DevOps, Kubernetes GPU clusters, etc. Some of the largest telco, CPG, pharma clients in the world. Heavy focus on Kubernetes (training, ELT, scheduler configs & plugins for GPU scheduling), including hybrid cloud k8s nodes.

Architect, design, implement, and optimize (Architecture and optimization of MLOps, AI DevOps, AI Observability) cloud-based AI, ML, Business Intelligence, DSS, and related solutions & infrastructures for diverse clients across a range of business requirements. Older experience in rule based expert systems (RBES’s). Architect cloud hybrid/migration/integration/edge compute integration to RBES/DSS & training LLM AI.

Develop and execute cloud migration strategies for complex Big Data, BI, ML (rule based through neural GPU, predictive, sentiment, diagnostic chatbot, LLM, GAN), assessing and optimizing ETL/KM applications for cloud deployment on Azure (7 years), AWS (12 years), and GCP (12 years). Focus on hybrid lift & shift, leveraging SAAS.

15+ years design, deploy, optimize scalable and cost-effective cloud architectures, ensuring high availability, security, and performance across all cloud provider’s Kubernetes, Docker, big data. Facebook/Meta, Pinterest, AT&T, Daimler/Bosch ADAS, Alphabet/Google, Amazon RedCloud, et al. Leveraging DevOps, MLOps, SecOps for 15 years.

Heavily involved in migration of data preprocessing, tagging, model training & related data pipeline work, e.g. leveraging multicloud spot instances.

Collaborate closely with stakeholders, including business leaders and data scientists, to identify requirements and align technical solutions with organizational goals.

Develop and implement AI and ML models to extract insights from large datasets, drive predictive analytics, and improve decision-making processes. First use of GAN’s leading to Mercedes/Bosch advances in ADAS 4, multiple implementations of deep(er) neural networks for faster predictive analytics (IBM Watson Earth Weather, Sikorsky Helicopter, AT&T, Verizon, multiple cell tower lessors. Call center implementations of advanced diagnostic ML, drug trials & LIMS LLM’s text analysis. Growing vertical AI solution pilots for service, technical, and sentiment business requirements (telco wireline & 5G ML).

Conduct thorough performance testing, troubleshooting, and optimization of cloud-based solutions to ensure optimal functionality.

Provide technical guidance and mentorship to junior team members, fostering their professional growth and development.

Work History Summary:

Anthropomorphics 2019 - Current

Consultant: AI Modernization Architect

Technical Practice Lead:

-Support all aspects of AI (Generative AI focus) data with a focus on generative, retraining, and public model tuning. Focus on Big Data IIOT, ERP (SAP/Oracle/D365) data integration, especially in supply chain, manufacturing. Pharma/BioPharma Laboratory Information Systems GenAI discovery, etc.

-Assist in GenAI driven changes to data warehousing technologies and data integration pipelines using both ELT and ETL processes supporting data warehouses, data lakes, and data meshes with a focus on AI data needs across sales, support, IIOT, manufacturing, vision.

-Experience with data modeling, including schema design, data models, data flow diagrams, data dictionaries and metadata repositories supporting structured, log format, and unstructured text/video/audio/imaging.

-Experience designing and building complex data solutions using both SQL and non- SQL databases, RAG Vector db’s, prompt engineering, etc.

-Experience with Application Programming Interface (API) for custom workflows, microservices, and integration

-Architecting and deploying Data Hub, Data Lake/house, Data Fabric, and Data Mesh concepts and hybrid (on premises + cloud) data infrastructures

-Knowledge of data science, machine learning, and statistical analysis techniques to build predictive models, perform advanced analytics, and derive actionable insights from data

-Experience and knowledge building Data Catalogs, Data Marts, Metadata repositories, APIM tools, etc.

-Experience collaborating with cross-functional teams to define data standards, guidelines, and best practices

-Knowledge of data governance, data security, and compliance standards.

-Excellent communication skills with the ability to convey complex, technical information in an understandable manner

-Familiar with data visualization tools (e.g., Tableau, Power BI), and data pipelines that incorporate them

-Familiar with AI capabilities across various proprietary and open source LLM’s, RAG, NAG and some experience in integration of Data Hub/Lake/Mesh with AI tools.

-Extensive engagements assessing and evaluating:

oBusiness goals and objectives

oGenAI driven data requirements and needs, both internal and external

oImpact of GenAI data complexities on current data infrastructure

oGenAI data sources, ETL/ELT transformations, integration points

oGenAI driven changes to Data Governance, Quality, and Compliance

oSecurity and Privacy Measures including GOV, MITRE, EU AI, etc. for AI attack surface and vulnerability management

oData Lifecycle Management including Big Data, IIOT, GenAI with legal impacts of PII, HIPAA, AI de-anonymization.

oMetadata and data cataloging required for advanced AI such as LLM, RAG, GAN.

-Support GenAI implementations in assessing and resolving scalability and performance improvements of ERP systems (SAP, Oracle, D365)

Modernize hybrid and public cloud client’s applications to leverage all aspects of AI with a focus on generative, retraining, and public model tuning. Focus on assisting clients and solution providers to build practices, architect, deliver, and optimize Machine Learning DevOps and Site Reliability/Observability in cloud/hybrid cloud: Kubernetes, hybrid/public/Edge, Run:AI, ML CI/CD best practices. Work with European Near-Shore providers around MLOps/SRE. Provide presales engagement support, SOW response, and post-sales architecture, debug, and implementation support related to big data ELT, ML CI/CD, DSS, practical AI, predictive ML, sentiment analysis, Azure, AWS, GCP.

Client Engagements:

Major IT Vendor: GenAI Advisory

-Co-develop GenAI Cybersecurity advisory consulting offering: scope, marketing/sales collateral, DoD/NIST, Data/Data Flows, GRC/Data Stewardship, AI including LLM/GenAI/RAG/GAN et al.

-Help client develop their internal AI Center of Excellence whose purpose is to enable AI modernization of the 4,000 apps in use, identifying 300+ applications which will be AI enhanced.

-Develop clients consulting practice for AI Modernization. Focus on solutions for private, data center data across their 17 worldwide data centers.

-Deliver readiness assessments for 93 internal AI projects, support sales cycle in providing assessments to customers (Pharma, LIMS, Finance and Stock/Bond trading) evaluating large GPU acquisitions for Kubernetes farms, Ai Architecture, design, data strategies, and integration of AI into existing processes.

-Guide GenAI related discussions with client C-level & Executives, including hallucination, GDRP, PII, HIPAA, training data leakage.

-Support specific application teams scaling GenAI for SAP Supply Chain, D365, Oracle Applications vi Data Mesh and ETL/ELT (private cloud & hybrid cloud)

-NVidia AI Enterprise, hybrid cloud Helix Validated Designs for hybrid cloud Generative AI machine learning solutions: AirFlow, Argo, Auto-gpt, AWS: Outpost & VMWare Cloud, Azure AutoGen, Azure: Stack HCI & Edge, Ceph, Chroma, Edge Cloud Orchestrator, FAISS, FastAPI, GCP Edge, Git Actions, GitRunners, Haystack, HuggingFace Nvidia NGC Catalog, Kubeflow, Kubernetes GPU Schedulers (nVidia, AMD), LabelBox, LangChain, LLMA Index, Milvus, Minio, MLFlow, NAG, Nvidia NEMO Guardrails, Pachyderm, Pinecone. Minio, Poolparty., Prodigy, RAN, Run:AI for Nvidia AI for VMWare, Synthetic Data, Tanzu Intelligence, TensorBoard, VMWare CloudFormation, Zillig

Telco MSP: AI Modernization

-DSS and ML to telcos in emerging markets: Work with CTO and team to rearchitect the existing open-source big data platform to hybrid Cloud SAAS (AWS, Azure, GCP) around ML Ops best practices. Identify opportunities around 5G, IIOS, MFG 4.0 leveraging current SAAS ML pipelines. Work with CEO and Heads of Sales teams on engagements in Dubai, UAE, Nigeria, Egypt. Extend existing predictive analytics and chat diagnostic RBES’s to leverage generative AI over new data.

-GCP: Design and instantiate pilot for 5 of one client’s 30+ opcos: (Terraform and GCloud) DataProc & DataFlow. Hive, Trino, Ranger integration to AD, etc. Support existing MLOps pipelines, assisting team to enable Google Vertex for Lamba out of band events. TPC-H benchmarks. Architect and configure Vertex AI, work with Autom8 to integrate.

-Azure: Design and instantiate pilot for another client’s (3 of 20) wire and wireless OpCo’s: Synapse, Fabric, Azure Data Lake (ADSL2), Event Hub, Event Grid, Pilot Azure Fabric & Azure Cognitive Services (text/sentiment), Perview (enable labeled data controls (PI/PII, government privacy controls) controlled search via Synapse, integration across Hive, various SQL’s, Oracle, operational and analytical stores), Hive (excluding complex Parquet/Avro), HDInsight’s, Hive Metastore, Starburst (ML Learning data lake), Hazelcast (in memory inference), Perview, TPC-H benchmarks.

-Training sessions for sales and technical teams: hybrid cloud big data, best practices for migrations, etc.

-Presales advisory for 3 Ligadata client’s BI/ML cloud modernizations (Generative, NAG, LLM, Kubernetes, GPU scheduler AMD/Nvidia), Terraform, ETL via NiFi/Kafka, etc.)

Major Cloud Provider: MLOps

-Technical integration engineer (DevOps/MLOps) supporting Google Cloud Telco in pilots for Ericsson, Nokia, Casa: onboarding of their 5G Core Network Functions to GDCE Kubernetes for various telco providers (Jio, Deutche Telekom + TMobile, Telus, TIM (Italy, Brazil)) in 5G Core on Kubernetes (GCP Edge), supporting 5G RAN test integration and Spirent RAN load testing. Validating, load & stress testing, CI/CD automation into Google Distributed Cloud Edge (GDCE) and hybrid cloud (GDCE/GKE): Provide security, k8s configurations for NF networking, Mellanox NIC’s, performance tuning, Helm chart support: Google Telco Solutions, Kubernetes, NF Networking.

-Telco Analytics Solutions: support integration (testing) Google’s Vertex AI Cloud to Edge for Telco RAN/MIMO and MEC optimization, training pipelines via DataProc & DataFlow.

Disk/SSD manufacturer: AI Optimization

-MLOps: Rearchitect virtualized HPC environment to improve throughput, 3x improvement in GPU utilization, 2x faster image recognition, observability improvements in client’s fab’s. Reduced fab error rates by 3-7%, increased accuracy and utilization of cell test system by 4x, reduced expedited shipment delivery costs by 2x.

-Support the migration from Red Hat Open Shift (Kubernetes) to Google GKE: Anthos GDCE (Kubernetes) for VMware (On Prem) + AWS EKS. Transitional support of a specialized OpenShift cluster running DPDK – Data Plane Development Kit for shared nVidia GPU’s (and debugging out of vector issues due to pod affinity defaults for very large nodes). Improving AI driven manufacturing insights & decision making, support the stabilization and migration of additional applications from VMWare: application (re)architecture, technology: buildout of Center of Excellence for Public/Hybrid/Private cloud. Resolve issues with IIOT image processing AI (Spark nVidia Tensor, 1200 to 200mscec improvement, increased ML parms), K8S Observability COE Chief Architect: DataIQ Integration, GCP, GCP Anthos Private Cloud for VMware, OpenShift Container Platform to Portworx, Anthos managed AWS EKS + GKS, AWS CI/CD Jenkins Pipelines, 3rd level OpenShift/Anthos/Kubernetes/Container/Networking/nVidia/VMware support. Hashicorp Vault, Active Intrusion Detection support, CI/CD code quality/Software Supply Chain Vuln testing, etc. AWS IAM, CloudWatch/Trails, Splunk, integration for EKS, Redshift, Cilium. External vendor (Workday, SAP, Oracle ERP) security and application integration technical architectures

-Technical architect/deployment support: supporting new and existing MLOps/IIoT/Digital Twin deployments to Fab data centers (GKE Anthos/VMware) Worldwide; DataIQ integration; Cloudera (CDP/CDF) on Kubernetes, Architect new AI systems into Kubernetes, Rancher, Confluence Kafka, NiFi, DataIQ, CDP Spark, nVidia VMware nodes. Support Looker ETL and query performance improvements.

-Own the technical relationships with AWS, Google, Portworx, Rancher for all operational, technical and architectural asks (FAAS, SAAS, some IAAS/PAAS).

-For the test cell analytics MLOps team(s), resolved scalability and performance issues around applications running in the pods, help team to optimize containers, code, work with GCloud to identify Kubelet configuration issues, Linux kernel (CNI, Contrack, & NAT) issues, improve training, improve Looker performance, etc.

-Improve application responsiveness by enhancing Kubernetes operators for MLOps training, inference exception eventing, monitoring, and complex Spark/Kafka/NiFI ELT needs.

-MLOps improvements for GKE (TensorFlow: TFU’s & GPU’s; VMWare/GKE, HP HPC), NiFi, Kafka, MongoDB, Elasticsearch for predictive analytics and event driven ML inference for various digital twin applications.

11 Fab’s (3 US, Israel, India, 2 Thailand, 2 China, 2 Japan) with collocated data centers, running 12 clusters of Anthos Kubernetes (GKE), ~2k K8S nodes, 1M pods, support subset of global business apps running in AWS and GCP, moving to Onprem Anthos, with global ML primarily in GCP, and general business in AWS: except for Fab based operations collocated due to 1-2 petabytes of daily data per fab, client is multicloud native (no data centers). VMware, Rancher, Portworx, EMC, NetApp. Spark, NiFi, Snowflake, DataBricks, DataIQ, Bitbucket, AWS EKS, GCP GKE, GKE Anthos VMWare, De-scheduler, Envoy, Prometheus, Splunk, CloudStrike, Grafana, ELK, Goldilocks, Fairwinds, Java, Go, Python, TensorFlow, VMWare, GKS Tesla GPU pod scheduling, Aero, Bitbucket, Artifactory, Airflow, Kafka (Confluent), Bitnami, AWS Redshift, Snap Logic (ERTL), EMR, Jenkins, Spinnaker, MongoDB, PostgreSQL, MySQL, Elasticsearch, AWS Redshift, Cilium, Pega (Supply Chain Analytics), EKS.

Major Telecoms Company: Cloud/AI Modernization

-Initially SME for Open Source Big Data ecosystem (DSS, ML) on Azure: Digital transformation of 5500 applications (75,000 systems) to Azure. AKS (Kubernetes) Subject Matter Expert team, heavy focus on securing Kubernetes/containers. Architect 400 remote clusters of Remote Kubernetes (5G MasterCore/EdgeCompute), K8S real time intrusion detection, SME supporting the migration to AKS (Terraform + Helm via DevOps pipelines – ML/DevOps) of existing AI, Azure Machine Learning, & “big data” components: Hadoop, HD Insights, Cassandra, Spark, Airflow, Snowflake, Packer/Docker, AKS and Azure SAAS (Azure AI, ML, Functions, Container Svc., IoT, DataBricks), etc. Leverage Terraform and Istio, Azure APIM, Linode (multicloud Kubernetes and IAAS). Support Terraform based Azure Containers and Azure Kubernetes Service based on Microsoft + Hashicorp developed Terraform tooling for Azure DevOps CI, extending for security in depth (security as code) controls (SELinux, ACL controls on load balancers, ingress & egress controllers, advanced configuration of Nginx, L5/L7 proxies, VPC peering, etc.

-MLOps application migration: architecture and implementation support migrating to Azure Kubernetes (nVidia GPU’s), scheduler migration (Run:Ai, Airflow), Terraform, for client’s wireline and wireless predictive analytics, various chatbots, and sentiment analysis applications. AKS, Azure Machine Learning/AML Studio, Run:AI for Kubernetes, Airflow, Terraform.

-5G: Architect and modify our Azure Terraform templates (GitHub Actions/Runners) to support Azure for Operators Cloud (IAAS, Kubernetes/AKS, Azure Container Services, Azure Modular Data Center (5G Edge), Azure API Management (AKS Services)), 5G MasterCore/EdgeCompute, Kubernetes real time IDS for edge compute.

Major Retailer: Online Presence

-MLOps/SRE Observability: Assess, recommend, and assist in bringing observability best practices to Walmart Online including the ML and DSS data flows. Improve utilization of web infrastructure under stress by 2x through improvements in CI test case coverage, Stress test automation at scale. Similar improvements to HPC utilization under load by 3x. (Hadoop, hBase, Cassandra, Spark, Airflow, nVidia T100’s, Kubernetes, Azure)

-SRE/PM: Pilot to Production model to improve slow AI/Data Science applications: work to accelerate AI projects to move to production in Azure, GCP. Leverage Azure Kubernetes, AKS Cloud Scheduler: resulting in higher quality suggestions, better ad insertion fees, 15% increase from partner ad revenue. H2O.ai (ML DevOps, Driverless AI), Looker. Azure ML, GCP BigTables, BigQuery, CloudSQL. ATP, Supply Chain. SAP integration (R/3, SCM, CM, BW).

Avanade (Accenture/Microsoft JV) 2018 - 2019

Title: Group Manager then Technical Practice Lead

Technical Group Manager through Technical Practice Lead:

Avanade COE for Site Reliability & Observability, Create and grow the practice. In addition to evangelizing DevOps and SRE, develop and grow the MLOps and ML Site Reliability practices areas around Azure and 3rd party offerings. Provide presales engagement support, SOW response, and post-sales architecture, debug, and implementation support for Avanade and Accenture engagements related to big data ELT, ML CI/CD, DSS, practical AI, predictive ML, sentiment analysis, Azure Chatbots.

Accenture AI & Analytics: Develop best practices for MLOps/MLDevOps, ELT, support presentations, participate in internal and client POC’s. MLOps & ML SRE architecture deliveries.

Accenture Digital Transformations Risk Management Office: participate in turnarounds of problem digital transformations; Risk Management Office reviews of various projects.

Practice Growth Activities:

Technical lead of (15+) Pilot to Production engagements: AI Ops, SecOps, DevOps Velocity, Agile vs. Waterfall, AKS/Docker migration, SAP on Azure, Data Lakes/Edge Analytics/BI/AI assisted BI. Led to 5 ($15M) new engagements and an estimated $8M uplift to existing engagements

15+ Microsoft Professional services Pilot to Production engagements via Education Delivery: Azure for Agile DevOps, Azure CI/CD, Azure IoT, Azure Big Data & Analytics Services/Synapse, etc.

10+ Azure SAP HANA Migration Reviews & assessments to improve SAP DevOps. 15% increase in pipeline within 90 days of sales team training

Identified an employee satisfaction improvement opportunity: shortfall in new-tech learning by existing staff when hiring outside for new talents (e.g. I was hired for my Big Data Ops SRE experience): Work with CFO, HR and key practice leads to start a 3% learning objective KPI that had the highest response from staff worldwide of any program ever.

Develop training and consulting material around CyberSecurity in depth for Docker and Kubernetes clusters and components.

Key engagements:

Leading Retail Azure transformation Azure: reduction of net new cross silo code development by 25%.

Leading Cloud (MSFT/Accenture JV) provider (20+ engagement workshops & classes) for DevOps at scale

Biopharma (US) Azure Big Data, Azure IoT, Big Data DevOps. Make LIMS, JV projects, R&D data fully searchable online (approx. 3PB of documents now searchable via semantic analysis)

Pharma (UK) Azure Big Data, Centrify, Azure Data Lake. From paper and raw pdf to fully semantically indexed document search improvements across all JV’s. ~2.5PB

Leading hospitality: MuleSoft ERP/AnyPoint, SAP R/3 to AWS, Kafka (HDF & Confluent), Informatica, Cassandra, Hybrid DevOps, AKS (Kubernetes, Docker). Reduced AWS spend by 3% while increasing throughput by 15%

Health Care: Azure DataLake, Azure BI, etc. for improved practitioner UX. MedTech and MD misclassification reduction by 75% resulting in substantial improvement in insurance provider payment turnaround

US Cellphone merger: presales RFP responsible for devops/MLOps capabilities. Won contract ($180M)

AMS US, EU 2013-2018

Title: Big Data Architect to AI Practice Lead

Key engagements:

Architecture Software (4000 subscriptions) (AWS)

Calif. Dept. of Education

Daimler Bosch ADAS

EMC/Pivotal

Fortuna Liebherr (EU)

Google Mapping acquisition (Waymo/Kubernetes)

Google Satellite Imaging Acquisition (Google Maps/Kubernetes+Borg)

IBM Watson Earth

JPMChase

Mobile banking provider (65% of all banks worldwide) (AWS)

Music Streaming Service (AWS)

Petroleum Company: Seismic Imaging

Petroleum Pipeline & Storage Services (AWS)

Petroleum Services Company (AWS)

Pinterest

RedCloud/Amazon

Surveillance Video (AWS)

Uber

Verizon

Video Enhanced Security (AWS)

Vodaphone

Ansys 2009 - 2013

Title: Senior Architect: Cloud Transformations. SAP Basis, Infrastructure

Develop “Pilot to Production” micro project model to rapidly grow the practice into new areas: SAP DevOps (BasisTechnologies partner), workshops, presentations: Given responsibility for 3rd party integration for SAP solutions (support presales, proposals, POC’s, and SAP BASIS delivery architect) for SAP Enterprise Portal (TopTier) engagements, and Salesforce (Force.com). Work with AWS and SAP to certify SAP for non-production systems (Hybrid Cloud), then work with AWS to market the solution as an exclusive AWS partner (with SAP AG). All engagements were P2P based growth. No big bang or major brown/green field projects!

Key engagements:

Aerospace (rotary wing) manufacturer – MLOps – AWS ($5M, $25M ROI first year)

Chemical Distributor (SAP DevOps AWS)

Computer equipment manufacturer

CPG conglomerate

Electric car manufacturer

Global Security Services Provider

Grocery Store Chain (Western US)

Major American car financing bank

Major computer storage & virtualization company

Major Medical equipment manufacturer

Major networking company: DevOps/Solution Architect (SAP AWS)

Major telecoms manufacturer - MLOps

Major US Bank

Major Utility (UK, US, Canada - $140M) – DevOps/MLOps – project turnaround ($60M)

Medical Electronics Manufacturer (Mexico, Brazil)

Multinational Beverage CPG

Multinational glass and ceramics manufacturer

Petroleum Field Services Provider (SAP DevOps AWS, MLOps)

Pharma (SAP PDC/AWS)

Semiconductor equipment manufacturer

US computer equipment manufacturer

US Government Agency

World’s largest vehicle manufacturer

Experience prior to 2009

AWS cloud, Agile, DevOps transformations, SAP Cloud, SAP HANA, SAP Technical through Practice Lead/CIO Advisory Practice: business and cloud transformation consulting (US, Asia, Middle East, UK, Germany, Ireland, Italy, France)

Teaching:

California Institute of Technology 2021/2022

Professor: School of Information Science Adjunct Professor

–Lectures: Cybersecurity, DevSecOps Practices

–Seminars: Cloud Transformation Advisory Lectures, Security in Depth, SRE/DevSecOps, Site Reliability Engineering, Multi-cloud Strategies

–Cybersecurity Supply Chain Lectures: Assess various Open-Source projects for code coverage, OWAS, CISA, etc. testing using AWS Code, Azure DevOps.

Education:

San Francisco State University

Computer Science – Artificial Intelligence/Finance dual major (1980-1984)

Shaftesbury University: London, England

Bachelor of Science – Computer Science 1989-1991

MBA – Finance and eCommerce - 2001

Certification/Training:

Agile Certified Practitioner (DSDM)

Agile SAFe:

AWS Certification: Certified AWS Architect (Accenture)

Azure Certifications: Azure Trainer, Azure Architect, Azure Security Engineer, Azure DevOps, Azure AI/Big Data, SAP HANA on Azure

Cisco UCS/vBlock (Cisco + NetApp) Certified Engineer

DevOps (OneOps: Azure DevOps, GCP DevOps)

GCP Certification: Certified GCP Architect

HortonWorks Certified HDP & HDF Architect, Admin

IBM Systems Engineer Certification – IBM AIX, HA/CMP

Microsoft Azure Partner Program Certified Solution Architect

Network Appliance Certified Engineer

nVidia Partner Certified Associate: AI/DC, Mellanox, Accelerated Computing Fundamentals, HPC containers, Data Science Workflows, GenAI, GNN, RNN, Bright Clusters

SAP BASIS, HANA Partner Engineer, HANA: Technical Certification, SAP OS/DB Migration Engineer

VMWare Certified Engineer

Classes Taught:

Agile processes for Big Data Transformations

AWS Infrastructure (Big Data DevOps, EMR (Hadoop/Spark), Redshift, Terraform)

Azure: 15+ Certification Classes/Training Workshops: Azure DevOps, Azure Kubernetes Service, Azure DataLakes, Azure Big Data, Azure Technology, Azure Architect, Azure IoT, Azure Security, SAP HANA on Azure

Hadoop, Hive, Spark, Spark Streaming, Kafka/Flume

SAP LVM, SAP LaMa, DevOps for SAP (SAP Cloud, Azure, AWS), SAP Basis, SAP GRC, BO GRC

University: Cloud Cybersecurity (2021)

University: Cloud Fundamentals (2021

University: DevSecOps (2021, 2022)

University: Computer Science (2021, 2022)

Citizenship: U.S.

Security Clearance: US Top Secret/EBI (expired, resubmission required)

Skills Matrix

Accenture Applied Intelligence Platform (AI, ML, ETL/ELT)

Agile processes for Big Data Transformations: Sprints, Kanban

Agile/DSDM

Apache Airflow, Flume, Hadoop, Hive, Spark, Spark Streaming, Kafka

Application & End User Monitoring (Dynatrace, New Relic, Splunk, SolarWinds)

Aqua IDS/IPS

AT&T Alien Labs Kubernetes IDS

AWS Big Data DevOps, EMR (Hadoop/Spark), Redshift, Terraform, DevOps, EC2, ECS, Lambda, API Gateway, Cloud Front, Cloud Watch, Kinesis, AMI

Azure: (Advanced Data Factory, Agile, AI, Big Data, CI/CD, Containers/Docker, AKS, Azure Private 5G Core, ADO/Azure DevOps)

CosmosDB, Data Lake Analytics, Data Lakes & Data Lake Store, Database for MySQL, Database migration service, DataBricks (Data Lake & Delta Engine), Azure DevOps, Docker, Edge, Event Bus/Event Hub, Functions, HDInsights (Hadoop Spark Kafka), IoT, Kubernetes/AKS, Machine Learning, PowerShell/Automation, Security, Stream Analytics, System Center

Bamboo

Bash

Cassandra (Apache, DataStax)

CircleCI

CloudBees

Confluence

Docker (Compose, Swarm, Packer)

Drupal

DSDM (Agile)

Elastic Search (also Logstash, Kibana, ELK)

Falco (K8S IDS)

Git, GitHub, GitLab

GNU Linux: RedHat, Ubuntu, SELinux, Alpine

GoLang/Go

Google Cloud/GCP (Anthos/VMWare, BigTables, BigQuery, Kubernetes/GKE, DevOps, DataFlow, DataProc, Anthos, Istio, Velostrata, Google Spanner, Google Compute Engine, GCE, Kubernetes, GKE, Big query, Cloud SQL, Cloud Run, Digital Run, App Engine, GCP Edge, Looker, Single Store DB)

H2O: ML DevOps, Driverless AI, beta of Q

HipChat

HortonWorks HDP & HDF Architect, Admin: Hadoop, Kafka, Spark, NiFi

Java

JavaScript, Node.js, NPM, etc.

Jira

Jupyter Notebooks, JupyterLab

Kafka (Azure, Hortonworks, Confluent, IBM, Kafka Proxies)

Kibana

Kubernetes (AWS, GCP, Azure), Anthos, Swarm, Helm, CNI’s, Cloud Cluster Manager, Multicloud, sidecars, ingress/egress controllers, Etcd, Istio, LinkerD, Calico/anetd

Linode (AWS, Azure, Linode Kubernetes)

Logstash

Matlab

Medusa, Nginx

MITRE ATT&CK Framework

MongoDB, MySQL, MariaDB, CosmosDB

MuleSoft

nVidia HPC, GenAI, Bright Clusters, Accelerated Computing

Network Appliance

NiFi (Apache, Hortonworks)

OneOps: Azure/GCP/OpenStack

Onyx Cloud Automation (Consona)

Oracle Cloud (Oracle Cloud services, Oracle Autonomous Database, Oracle Autonomous Linux, various Oracle Cloud Applications)

Oracle RAC/DBA, ODB, GoldenGate

Packer

Palo Alto Networks, Prisma Cloud

PMI (PMP)

PostMan

Project Management Professional

Python, Python ML libraries (varying currency,

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