Pablo S. Email & Phone Number

Los Angeles, Ca, Us

San Francisco, Ca, Us

I worked on the whole range of use cases provided by databricks:1) Data engineering2) Data ingestion, transformation and delivery3) Machine learning, feature stores, model serving4) GenAI, LLMs. A lot of GenAI5) Data cataloguing and governance

Boston, Massachusetts, Us

San Francisco, Ca, Us

I did a lot of things at AppDynamics. In a nutshell, I had an idea, I built a team around it and the team delivered $100M+ in revenue impact in 3 years of operating.1) I started as a Sales Engineer where I closed some of the biggest deals at the time2) I redesigned my job (from SE to Field Architect) to more proactively manage technical and deal risk across the whole of AppDynamics' Western region. In the quarters where I acted as an individual contributor I impacted 10% of the revenue in a region of 40+ Sales Engineers3) During this time I worked on a side project (just for kicks) that eventually became part of our Machine Learning engine to automatically analyze root cause of performance slowdowns (see attached abstract)4) Based on the success of the role I created, I was given the opportunity to start a team of Field Architects based on my job redesign and philosophy of proactively managing and impacting risk and revenue across regions. I started in the Western region and eventually recruited and grew the team from scratch to support all regions in North America and LATAM5) With the help and input of the team, we expanded to various strategic functions across AppDynamics. This includes product collaboration, SE enablement and a center of excellence for the field. During this time, in its core function, the team has impacted 20% of the revenue in their regions despite only being 5% of the workforce6) The core functions of the team have expanded into the APAC region and are currently being stood up in EMEA, which now makes the original idea of Field Architecture a global function inside AppDynamics

San Francisco, Ca, Us

San Francisco, Ca, Us

As a side project, I worked on some Machine Learning to automatically analyze code performance in transactions. A redacted summary is attached. This work eventually became part of AppDynamics' AI engine for automatically analyzing root cause analysis of performance problems

San Francisco, Ca, Us

Application performance for all kinds of distributed applications:Java.NETNode.jsC++gdb, jdb, WinDBGDecompiling Java, .NET and C++NoSQL - Redis, Mongo, etc...DBs - Oracle, SQL Server, MySQL, etc...Messaging - JMS, TibcoOther things...

Ottawa, Ontario, Ca

1) Was the main SE closing the biggest deal in the company's history at $10M. The customer is América Móvil the holding company for most major telcos and cloud providers in all of Latin America. The deal included software and services for delivering IaaS, SaaS and cloud services from 4 data centers in Latin America covering Telmex (Mexico), Claro Argentina, Claro Chile, Embratel (Brazil) and other, smaller markets.2) Was the lone SE closing another top 5 deal in the US for AT&T - worth $3M3) Led the technical planning and development of the IBM relationship, Parallels'​ biggest and most important partner4) President's clubOn the technical side, my expertise at Parallels ranges the entire infrastructure stack:1) Recommending hardware/networking equipment, layout and configuration for data center infrastructure2) Designing, testing and performance tuning a distributed storage layer (clustered file system)3) Virtualization and OS layer - Linux and Windows/HW and kernel virtualization4) Application layer - working with customers to optimize their workloads on the Parallels stack5) Automation/Orchestration - Automation of the infrastructure for providing cloud services - IaaS, SaaS, DaaS, etc...Some technologies that I am familiar/expert with:Linux:RHEL, CentOS, UbuntuLinux KernelLinux configuration/SysadminLinux Tools - Puppet, shell, Python, others...Windows:Windows Server 2003-2012Windows KernelWinDbgVisual StudioActive DirectorySQL ServerVB.NETASP.NETVirtualization:Hardware Virtualization (Hypervisor) - Parallels Cloud Server, KVM, SRIOV, GPU virtualizationKernel Virtualization (Container) - Parallels Containers, DockerStorage:Clustered file systemsDistributed storagePhysical storageCloud Orchestration:OpenStackNetworking:Overlay networksVLANVXLANOpenVswitchLinux TCP stackProgramming:.NETC++XML/REST/SOAPHardware:x86_64IBM PureFlexVCE VBlockCisco UCSData center infrastructure

Statistical machine learningNatural Language Processing (NLP)SaaS

Sunnyvale, Ca, Us

Optimization through analyticsData mining - clustering, regression, time series, random distributionsAnalytics automationBehavioral targetingSearch & Display advertising

Los Angeles, Ca, Us

Great times

All things regression and load testingGreat times

Computational fluid dynamicsFinite element modelingGood times

B.S., Mechanical & Aerospace Engineering

Master Of Engineering, Aerospace Engineering

Mba, Marketing And Finance