At Tesla I've been playing a cross-functional engineering role - working on critical in-house software engineering projects.

Given the nature of Tesla's stack .... that's about all I can say :).

Leading a variety of productized, open technologies that are essential to the VMWare Tanzu Portfolio, specifically around:
- Antrea (our CNI)
- Kubernetes on Windows
- Release Engineering and Conformance Testing
- Edge compute offering

As an engineering leader at VMWare I serve in the following capacities:

- Engineering Lead for "Thick" Edge and Antrea Kubernetes related initiatives at VMWare.
- Engineering Lead for Kubernetes on Windows (VMWare Tanzu) and our broader Extended Infrastructure initiative. Brought Windows from a POC to a fully supported TKG feature, defined upstream and downstream SLAs around windows. Defining windows conformance for the world https://github.com/kubernetes/enhancements/issues/2578 .
- Managing customer escalations around networking, windows , and CNI providers, some of which were extremely time and business sensitive.
- Building teams, pairing w/ new engineers, keeping morale high in the face of continuous change, creating a culture of radical transparency, continuous collaboration, and openness, every day.

Meanwhile, I spend alot of time in the K8s community, driving several upstream initiatives:

- TL for sig-windows (CNCF) - working on the windows conformance initiative
- Lead for several sig-network (CNCF) sub projects, started both the network policy and kube proxy refactoring initiatives.
- Windows Conformance https://github.com/kubernetes/enhancements/tree/master/keps/sig-windows/2578-windows-conformance
- Network Policy Validation https://github.com/kubernetes/enhancements/tree/master/keps/sig-network/1611-network-policy-validation
- Default Namespace labels: https://github.com/kubernetes/enhancements/tree/master/keps/sig-api-machinery/2161-apiserver-default-labels

- Note I Joined in 2021 as an MTS4, was promoted to a Staff Enginneer in 2022... as an MTS4 my main focus was on Upstream K8s networking, Antrea as a CNI, and initial investments into TKG Window

Just joined my newest startup !

I'm working on a combination of up and downstream work on our K8s product line. 

Recent K8s projects include, https://github.com/carbonrelay/kapture, a Kafka+BigPetStore based load generation library for upstream performance testing of BigData workloads on kubernetes.

Also doing work on various storage and cluster bootstrapping algorithms for kubernetes distributions, and making sure our customers are happy :).

Cloud Native architect and lead for the entire synopsys suite of software products.   Admission: Architect titles always scare me.  But I think I was the "good kind of architect", enabling teams as opposed to holding them back.

Transitioned Blackducks entire deployment stack to a cloud native  SaaS (k8s on GKE, open shift, driven by an operator), built on 3 core products: our SAAS offering, OpsSight for container scanning at data center scale, and our cloud native product offering for on prem. 

- Built, grew, and trained a team of 6 engineers that had virtually no kubernetes experience to being core cloud native team.

-  Built and redesigned all cloud native offerings, unified as a single solution: The blackduck operator, driving our SaaS  (100+ customers, 100,000,000$ in business) as well as other products.

- Built the team and architecture for the OpsSight Connector (Perceptor) Product: Co-creator of the Perceptor open source platform for cloud native event response, scanning at data center scales, built around its original downstream product,  OpsSight scanner.

- Relentless customer support for all products for my team: creating a direct line of sight from customer driven insights to engineering R&D and implementation.  Ported 10s of major customers to on-premise OpenShift and Kubernetes offerings.

- Ported a complex, purely docker based application to a cloud native, unprivileged, kubernetes/openshift offering, including  putting specific patches into our products microservices so that they behaved better (i.e. least-privileged, backoff capabilities) in a highly secured and commoditized CPU/memory environments.

- Drove our cloud native offerings  adoption with several fortune 500 customers, helping them both adopt and embrace their own changing internal infrastructure alongside the idiosyncracies of our own cloud native security scanning offering (the blackduck hub).   Whitegloved customers with end to end kubernetes support: from debugging IPTables and DNS platform issues to distributed storage.

- Design, engineering, and internal training on a continous delivery and ephemeral infrastructure pipeline from scratch for verifying cloud native application offerings on all major platforms (openshift, kubernetes, swarm).   

- Open sourced several aspects of the business that needed to have broader transparency and ease of adoption in order to be recognized as valid products by customer segments.

-  Ported all infrastructure to terraform deployments, which  deployed kubernetes using kubeadm on EC2, VMWare, and GCE.  Ultimately this saved the company upwards of 20,000$ a month - and led to the entire team of 50+ engineers using an internal version of our customer SAAS offering for performance and feature testing.  This platform supported kubernetes, openshift, and docker swarm.

Deep technical and distributed systems, community driven engineering which evolved the kubernetes, glusterfs, and hadoop ecosystems in large part towards what they are today.

Kuberenetes/Openshift: Engineer

Worked  on core portions of Google's Kubernetes container platform and Red Hat OpenShift. 

- Distributed systems engineer. contributor and maintainer on Kubernetes platform (mostly golang).  Contributed core features to the HTTP client performance, high availability tooling, developer automation, and E2E testing suites, lead and/or participated in several SIG's with the community.

- Implemented several performance tweaks, optimizations ,  algorithm improvements to the kubernetes scheduler, including scale, performance, and cache optimizations which are only discoverable in large deployments / clusters of 1000s of nodes/pods.

- Mentored and trained several new developers on the internals of idiomatic kubernetes development and community practices, golang tooling, and on kubernetes framework engineering internals.

- One of the major contributors to kubernetes itself for the first 2 years of its existence.

- Contributed to and architected a broad range of product integration technologies in the bigdata ecosystem, under the Apache Software Foundation: Hadoop, Spark, Cassandra engineering  on alternative storage systems, middleware, mostly powered by GlusterFS/HDFS.

- Worked in several ASF projects and communities on behalf of Red Hat to increase our interop with open source big data projects, particularly in the Hadoop ecosystem (specifically BigTop, Apache Hadoop). Also wrote open source blueprints for internal evaluation and testing of Flink, Spark, Hadoop.

- Worked at the intersection of our interests in middleware, scalability, and bigdata, building automation and POCs around containerized I/O between big data frameworks (i.e. spark) and middleware data abstractions (TEEID/JDV).

- Built out the GlusterFS integration solution for Apache Hadoop used in Red Hat Storage as an HDFS alternative.  Worked with the broader hadoop community to make sure its test coverage was across the entire ecosystem of filesystem semantics (HBase, Hive, Mahout, and so on).

- Built one of the first containerized, generic SparkStreaming blueprint applications (forked and used by 100s of individual developers) and other blueprint applications for bootstrapping bigdata workflows.

- Mentoring and training developers on integration testing for the hadoop ecosystem, microservice architectures, reproducible deployments with vagrant, internal cloud usage.  Also spent a large amount of time with development tooling and engineering higher quality internal application blueprints and deployments.

ASF BigTop, ASF Hadoop

- Developed, reviewed, maintained code in the ASF as a PMC and Commiter : Apache BigTop (the open source hadoop distribution), and Apache CTakes (the medical text analytics framework).

- Engineered, and maintained large components of ASF  BigTop deployment, Integration and Smoke testing frameworks.

Synthetic Data Set Generation and Scale Testing for the ASF

- Built out the BigPetStore application (spark and mapreduce ecosystem apps w/ a synthetic, scale-out data generator).

- Reproducibility engineering around hadoop deployments: Architected complete end-to-end vagrant implementations of Apache BigTop for rapid prototyping and testing of new hadoop ecosystem releases.  Also lead the initiative porting ASF BigTop to Docker  for container based deployment and testing.

Scaling out CTakes for drug entity extraction at large scales

-  Contributed core containerization and scalability initiatives to the Apache CTakes project. 

Leading the the HCFS initiative for GlusterFS and Hadoop

- Filesystem and verification improvements across ASF hadoop and ASF bigtop as part of the HCFS initiative (https://wiki.apache.org/hadoop/HCFS/). 

- Became a Commiter/PMC in 2016, and later a Member of the ASF in March of 2017

Data (Hadoop) Engineering @ PeerIndex

- Engineered Java and Hadoop pipeline MapReduce PISAE (Peerindex social action engine) platform. Development of our backend MapReduce java systems - largely based on ingestion and feature extraction.

- Enabled Real time streaming for tweets from high profile social entities; EMR and hadoop administratoin on an as needed basis, for 200+ node clusters.2

- In addition to all the deployment and engineering work, founded a consulting firm, Rudolf Inc. Managed all financial affairs and contracts, presented, delivered technical solutions in the bigdata and web-data spaces to various multi-million dollar companies in Europe and the United States.

Founder  @ Rudolf Inc

- Reported directly to the Head of Research and CTO @peerindex on BigData pipeline, status, and implementing architecture changes.

- Coordinated the launch of our new site which was completely driven using a key-value storage (DynamoDB) and HDFS data backend,  millisecond latency SLAs.

- Implemented algorithms alongside data scientists, engineering directors, and the front-end team to ensure that data quality standards for 100s of millions of outputs were always met using a rock solid data model contract.

Various one-off solutions built for small / starter companies and academic labs.

- Reverse engineering of UML design for various specifications in accountancy systems for clients, key for scaling engineering efforts across teams at the time.

- Designed custom LISP / Python applications for ensuring transaction integrity  in complex, multi-database MySQL federated systems.

- Evaluated of e-commerce solutions (i.e. google checkout, paypal) with home grown product inventory and management systems (seikelceramics.com)

- Built Full stack, rapid software prototying, informatics consulting, and helping individuals get up to speed with data mining and machine learning related initiatives.

- Bioinformatics Consulting with UNLV's Biomedical Sciences department on protein analytics, literature mining software.

Designing Bioinformatics federation platforms

- Developer/designer of a highly interactive client side application for fully integrated molecular visualization platform (VENN) which allows for Jmol based 3D analysis of protein evolutionary conservation (See Publications). Created a cross platform VM for NMR data processing (vagrant, virtualbox, and ubuntu).

- Deployed plug-in based modules for implementation of molecular analysis algorithms in a single computational proteomics framework. Optimized and changed features of the application to suit emergent needs, such as protein domain oriented analyses.

- Data Warehousing/Modelling of Functional Minimotifs Designed a Hibernate API and MySQL data repository along with an java based which integrated proteomic information spanning protein motifs, functional annotations, taxonomy data, sequences, and protein domains.

- Architected an Expert System (MIMOSA) which automatically implemented various text mining and correlation scoring algorithms using ontologies for 5,000,000 publically available medical abstracts. Developed a plug in oriented Graphical User Interface using the Java Swing framework which enabled database driven, high throughput annotation of "minimotifs".

End to End Workflow Engineering Solutions  for Protein NMR Analysis 

- Collaborated on several database aspects of the NIH funded, publically available, web based Minimotif miner application (http://mnm.engr.uconn.edu). Engineered Java API's for reading/writing of large, binary FID representations present in vendor-specific NMR spectral data types in support of an open-source translation and conversion API.

- Built a Swing-based workflow building environment for time domain NMR data processing, as a custom, visual, 2D graphical application which allowed for on the fly creation of data-processing "actors", with reloadable and persistent state and associated, workflows which triggered offline data processing tasks.  All based on a finite state machine.

- Designed, architected of an integrated NMR visual data mining platform, as part of the Rudolf project using and Clojure to wrap existing Java API's.

- Presented work at premier scientific conferences at conferences (ICBMRS, Protein Folding Symposium, New England Structural Biology, Exp Nuclear Magnetic processing conference).

Proteomics data federation apps; published several (10+) articles in medium/high tier journals on algorithmic and visualization advances in data-integration of medical, biological, genomic data.  Computational protein analysis structure, sequence, and functional analysis; workflow builders for NMR data processing and annotation of peptide sequences with respect to phenotypes, medical conditions.

Created an NMR software integration environment for protein structure calculation and data processing.  This led to a PhD and several other adventures at the interface of data visualization, integration, and bioinformatics.

Mathematics (major) & Computer Science (minor).