Alan Whitehead

Enterprise sales / AI & infrastructure

I sell complex
technology—
and build with it.

I’m Alan Whitehead. I moved from technical account management at BlackBerry into enterprise sales in 2008 and have since won seven-figure agreements with universities and regulated institutions. Today I also run AI-agent and infrastructure systems hands-on: choosing the models, setting the boundaries, and verifying what the agents build.

25+ years in technology.
Enterprise sales since 2008.

01 / Experience mapSelect a connection ↙
01Enterprise salesInstitutions & public sector 02Technical trustSecurity, risk & procurement 03Systems & AIBuilt & run hands-on

The commercial record

Seven-figure SaaS agreements, a $10M+ territory, and a public-sector pipeline built from an unmapped territory.

Explore the deals

The connection between them

Institutions rarely buy features. They buy confidence through security review, migration risk, and procurement.

Inside a system-wide procurement win

The hands-on work

AI agents working inside defined boundaries, models chosen per task, and infrastructure whose recovery is proven with evidence.

Explore the technical work

Santa Monica, CA · Open to senior enterprise sales, strategic account, and business development roles

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$1M+Annual quota exceeded
President’s Club $10M+Territory owned
Regional VP, 50+ accounts Seven-figureCommercial outcome
Long-term agreement $2.5M+Pipeline built
Under 12 months

02 / Selected work

Where the two
sides meet.

One institutional agreement won against an entrenched incumbent. One business whose operations I rebuilt around connected systems.

Enterprise sales / Learning Management Systems

Replace the system.
Earn the institution’s trust.

A six-month RFP. A full-day, 50-stakeholder demonstration. A deeply embedded homegrown incumbent.

Client work / 2024–Present

Connect the tools.
Make the business work.

CRM routing, automated pricing, invoicing, and customer payments for an established field-services business.

See all selected deals

03 / Current technical work

Real systems,
run with discipline.

I run a Proxmox environment of more than 30 virtual machines and containers, and the systems that observe, deploy, and recover it. AI agents implement much of that work inside a harness I define. I choose the model and reasoning depth for each stage, have a different model review the result, and make the consequential calls.

It is personal infrastructure, not enterprise production. The discipline is what carries into a customer conversation.

Inside the systems
01Operational control planePython service · Least-privilege APIs · Staged releases02Backup & recovery programAudit · Runbooks · Restore validation03Agent harnessesBoundaries · Exit gates · Independent review04Multi-model workflowsModel and reasoning depth chosen per task

04 / The through line

Technical roots.
Commercial range.

Each step moved closer to the commercial decision without leaving the technology behind: from IT, to technical customer relationships, to enterprise sales, territories, and seven-figure agreements. The common thread is trust: understanding complex technology well enough to lower the risk of adopting it, whether a customer is buying it or I am running it.

Read the full career
  1. c. 1998IT & technology

    Community college IT, then roles including Unisys.

  2. 2004–2008Senior Technical Account Manager

    Research In Motion / BlackBerry. A technical, customer-facing foundation.

  3. 2008–2012Enterprise sales, BlackBerry

    Government and strategic accounts in Asia Pacific, then Senior Account Executive in the United States from 2009.

  4. 2012–2019Institutional SaaS sales & Regional VP

    D2L, selling Learning Management Systems and EdTech to Higher Education, then Regional VP of Sales, US West, at ProctorU (now Meazure Learning).

  5. 2023–2024Cyberbit, SLED

    Cybersecurity SaaS pipeline development and finalist-stage RFPs with State, Local, and Education customers, after a 2019–2023 family caregiving break.

  6. 2024–PresentIndependent technology work

    Field-services modernization for a client, and hands-on AI and infrastructure systems.

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and understand it?

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