You want someone who reads the stack and sees what's missing. Not just what's running.
Kyle Baudour — 8+ years marketing operations, Adobe Certified Expert in Marketo, PMP. I read the JD and built a working MarTech stack audit tool with an AI analysis layer instead of writing a cover letter.
Full resume on LinkedIn
MarTech Stack Intelligence
A synthetic stack inventory — 20 tools, 30 integration pairs, annual costs, renewal dates, AI feature availability — lives in a Google Sheet. A Claude-powered analysis layer reads the current state and returns a stack health score, AI adoption gap analysis, integration silos, redundancy flags, renewal alerts, and ranked recommendations as structured JSON. The frontend renders that analysis alongside the raw inventory data.
Free tiers throughout. Monthly operating cost at light traffic: under $1 in Claude API usage.
On the AI piece.
The JD asks for someone who identifies opportunities for AI and automation adoption and potentially leads an AI integration initiative to automate tasks, enhance analysis, and personalize at scale. The demo is a direct answer — not described, demonstrated. Claude reads the stack inventory and surfaces which tools have AI features sitting unused, where automatable integrations are still manual, and what to prioritize before the next renewal cycle. The model routing decision was deliberate: Haiku handles structured-output analysis on a tight JSON schema cleanly and for under a dollar a month at this traffic level. That's the kind of judgment call this role makes at scale.
On the MOps piece.
Eight years running marketing technology at the platform level — Marketo, Salesforce, Pardot, Dynamics 365, AEM, Workfront. Adobe Certified Expert in Marketo Engage. Pardot Specialist from Salesforce. PMP. The largest implementation in that run was a 26-country, 14-language AEM rollout at QuidelOrtho with three direct reports and more than 50 stakeholders across marketing, IT, legal, and regional teams. That kind of rollout lives or dies on the relationship between marketing requirements and IT execution — which is exactly what the JD's "primary liaison to IT" language describes.
On the systems piece.
The instinct on every MarTech problem is to ask what the repeatable system looks like. Not just the fix for today. The demo is a small version of that thinking: seed script, fixture fallback, structured analysis schema, renewal alert logic built into the data model from the start. The same pattern applies to Workfront intake workflows, Salesforce routing rules, data governance frameworks. The goal is always something the next person can operate without reverse-engineering your decisions.
Adobe Certified Expert · Marketo Engage
Also holding Pardot Specialist (Salesforce), PMP, CAPM, PSM I, PSM II, PSPO I, and AI Prompt Engineering (PMI). Certifications reflect the platforms I've run in production, not studied for a test.
26 countries. 14 languages. Three direct reports.
Led the QuidelOrtho AEM rollout across global markets — Sites, Assets, DAM, Workfront — with three direct reports and 50+ cross-functional stakeholders. Enterprise MarTech at the architecture level.
Claude, OpenAI, and the tools around them.
Currently running an independent Marketing Technology + AI Consulting practice. Building AI-powered operational systems for solo operators and small businesses. The demo is one artifact of that practice.
The full MarTech toolkit.
Marketo, Salesforce, Pardot, Eloqua-adjacent (Dynamics 365 MAP), AEM Sites/Assets, Adobe DAM, Workfront, 6Sense, Drift, Tableau, Power BI, SQL, Jira. API integrations. 8+ years, 10+ from 2014.
AI adoption gap analysis. The demo surfaces every tool in the stack that has AI features available but not in use — names them, describes what those features would unlock, and estimates activation effort. This is the JD's "identifying opportunities for adoption of AI and automation tools where they add value" in working form.
Integration health and silo detection. The integrations tab maps every tool pair — native, API, middleware, manual, or none. Claude flags the siloed tools, the manual workarounds standing in for native connections, and the data gaps that compound over time. This is the IT liaison work made visible.
Renewal intelligence and governance. Upcoming contract renewals surface with renew, renegotiate, or sunset recommendations attached. The data model includes ownership, utilization scores, and cost per tool. This is the business case infrastructure the JD asks for when it says "evaluate new marketing technologies and build business cases."
Stack health scoring. A 0-100 score with label summarizes overall stack state — utilization coverage, integration density, AI adoption rate, redundancy risk. One number to put in a CMO update, with the full breakdown one click below.
In production the source becomes a live vendor management system or a Workfront project registry. The schedule runs weekly. Claude outputs write to Slack, a read-only Confluence page, or a CMO dashboard. Renewal alerts fire 90 and 30 days out. Governance lives in the schema: canonical definitions, owned fields, versioned changes.