Be the architect of the automation that turns signals into pipeline.
AI is changing how companies grow—and marketing is next. At Concord, we’re not just automating tasks; we’re building a new category: connected multi-tool AI workflows that help teams move faster and convert engagement into revenue.
This role doesn’t exist in most companies yet. In 3–5 years, it will be core to how modern orgs launch and scale. Right now, you get to help define it.
About Concord
We’re an AI‑first company building the Model Context Protocol (MCP) infrastructure that will make traditional contract management obsolete. While others experiment with tools, we’re creating the protocols, connectors, and systems that will become industry standards.
We’ve already gained traction with 1,500+ companies and over 1M users—but we’re just getting started. The next phase will fundamentally change how businesses sell, support, and scale.
If you like moving fast, using the newest models, and solving problems no one has solved yet—you’ll thrive here. If you need detailed playbooks and predictable tasks… probably not.
This role is not for you if…
If you’re looking for:
A front-end job writing public-facing messaging for the company
A role that’s more focused on tweaking copy than building automation
A job where you don’t have to constantly test and iterate new workflows
A position where you’ll have weeks to fine-tune every idea
…then this role will frustrate you.
This role is for you if…
You thrive on:
Building back‑end systems that make marketers faster
Using AI to connect tools and trigger the right actions at the right time
Doing your own research—reading docs, joining customer calls, digging into data
Working as a maker who ships and improves every week
About the role
As our AI Marketing Architect (reporting to the GTM Engineer Lead), you will build and run the back-end automation that powers our marketing team. About half your time will be systems and agents; the other half will be hands‑on setup, testing, and improvements.
You will connect HubSpot, Google Analytics, Framer, and other tools; build small agents with MCP connectors; and make sure leads move from MQL → SQL → customer with less manual work and faster response.
What you’ll drive (missions, not chores)
- Connect the stack with MCP. Use MCP connectors to join our product signals, website, forms, webinars, and HubSpot into a single AI workflow layer. When a signal arrives, trigger the next step automatically—enrich, score, dedupe, route to SDR, or start the right nurture. Document how front‑end teammates can add new no‑code automations.
- Keep a live audience profile. Maintain an always‑updating profile of accounts and users (role, plan, feature usage, intent). Use LLMs to infer persona and needs. Expose real‑time segments and a “best next message” automation that website, email, ads, and chat can call for tailored copy.
- Run a template + asset factory. Own prompt packs and message templates that turn one approved message into many assets in a day—emails, Framer page sections, social posts, short video scripts, and demo outlines. Auto‑generate role/industry variants, apply naming/taxonomy rules, and push to HubSpot and Framer with one command.
- Automate demos and events. Build a demo data generator that seeds realistic accounts, toggles features, and resets with one click. Pair it with a webinar/event agent that creates landing pages, reminders, join links, clips recordings, and routes follow‑ups by segment—no manual stitching.
- Make testing and attribution simple. Ship an LLM assistant that proposes experiments, creates A/B and holdout tests across channels, and writes a short results memo. Apply UTM and campaign naming rules automatically. Publish self‑serve attribution in GA and HubSpot that the team trusts—from view to MQL to SQL to revenue.
What you bring
- 2–5 years in marketing ops, growth engineering, or automation (skill proof matters more than years)
- Ability to use AI tools (ChatGPT, Claude, Perplexity, and others) and to build agents with MCP connectors
- Tool fluency: HubSpot, Google Analytics, Framer; Appcues is a plus
- Confidence with APIs, webhooks, and basic scripting (JavaScript or Python); HTML/CSS for website updates
- Understanding of lifecycle models (contacts, companies, deals) and the path from MQL to SQL to customer
- Clear writing and documentation; steady habits for testing and version control
Why this is different
- You’ll connect AI tools in ways most companies won’t even think about for years
- Your “colleagues” will include AI agents you helped design
- The playbook isn’t written—you’ll help write it
- The impact is direct: your work reduces manual steps and creates qualified pipeline
Important information
- Location: Austin, TX. This role is full‑time in‑office at our Austin HQ (Northwest Hills)
If you’ve been waiting to prove how AI‑driven automation grows pipeline—this is your boarding call.
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