Technology leader
A technical leader with a linguist's ear and an architect's rigor. I find the real problem, and build the teams that solve it.
In plain terms: I turn "that sounds complicated" into "let's do it."
Technical leader · team builder · 20 years in enterprise pre- and post-sales
About
How I got here
Languages were the first thing I loved: how they work, and how differently they solve the same problems. That took me from general linguistics into computational linguistics, which is where it became a job — ontologies, taxonomies, enterprise search, back when getting a computer to understand a question meant months of hand-tuning. Solution engineering came next, then architecture, and eventually running teams. The first part never changed: understand the problem properly. It's still where I spend most of my time.
What I bring
Three things I'm good at
Building teams
I built a team of ten technical architects for enterprise engagements. I've taken engineers with no platform background and coached them into people other teams request by name.
Discovery
I don't start with a solution. I design the intake process, set the evaluation criteria, and ask the questions that surface what a customer needs, which is usually not what they asked for.
Technical depth
I go deep rather than staying at the slide layer: agentic AI, platform integrations, data architecture. I pick up new tools fast, and I'd rather read the docs than wait for an enablement session.
Career
Where I've been
Director, Technical Architects · Salesforce
Lead a team of 10 technical architects on enterprise Healthcare & Life Sciences accounts. Launched a dedicated team driving customer POC success for Agentforce (agentic AI) and Data 360.
Principal Solution Engineer / Team Lead · Salesforce
Service Cloud across Enterprise, Financial Services, and Healthcare & Life Sciences. Stood up and coached a new specialist team, mentoring engineers with no prior Salesforce experience.
Sr. Sales Consultant · Oracle
Led discovery, solution design, and custom demos for technical and C-level audiences across North America, including early integrations with chatbots and virtual assistants.
NLP & Enterprise Search · InQuira → Oracle · Infogain
Designed the ontologies, taxonomies, and content architectures behind enterprise NLP and search systems.
Outside work
Community work
Unpaid, ongoing, and the work I'm proudest of.
Pro-bono systems architecture
For four years I designed and built a custom Salesforce platform, pro bono, for a nonprofit supporting young adults with physical disabilities. It handles intake, program matching, participation tracking and donations.
Founding a global community
I co-founded an employee resource group at Salesforce. Making the case to leadership took a year. It now spans four regions and around 1,500 people, and I still set the strategy.
Board service
I sit on the board of a nonprofit that funds education, healthcare, and food assistance for underrepresented communities, advising leadership on strategy, fundraising and growth.
Exploring
What's piqued my curiosity
Not resume bullets. Just what has my attention right now.
CX & contact center
Conversational AI, back to my roots
Years before LLMs I was designing self-service and contact-center systems: chatbots, virtual assistants, knowledge search. Most of it disappointed. Watching conversational AI finally clear that bar is strange and satisfying, and I keep asking what good automated support looks like now that the agent can reason.
Semantic data
Knowledge graphs
This is the ontology and taxonomy work I used to tune by hand, except now it scales and feeds modern AI. I'm digging into how far that goes.
AI & security
AI-agent governance and security
Once an agent can call tools and remember things, it can be talked into using them by whatever it happens to read. Prompt injection, tool misuse, memory poisoning. I'm following the OWASP Agentic Top 10 and reading up on least-privilege tooling, approval gates and audit trails.
About this site
How this site got made
I built it with Claude — HTML, CSS, all of it. I've spent twenty years writing specs for machines that process language, and this was the first time one wrote back. What surprised me is how much of it was still the old job: saying precisely what I meant, and noticing when I'd been handed something plausible instead of something correct.
Say hello
Email is fastest, and it comes straight to me.
anna@annaknoll.com