Marketing Operations Specialist - AI & Automation

Overview

You'll build AI-powered automation workflows and optimize marketing systems at Checkmarx, a 1,000-person application security company. You report to a marketing ops leader who's extremely technical (6x Marketo Champion), working on automation projects that impact sales, marketing, and customer success teams. You'll spend your time in Marketo, CRM integrations, data pipelines, and testing AI tools to see what actually works.

Role Snapshot

Company Context

Stage: Mature/Late-stage (996 employees)

Product: Application security platform (Checkmarx One) - scans code for vulnerabilities, integrates into SDLC

Market: Enterprise AppSec space - selling to security teams, DevOps, engineering leaders

Buyer Complexity: Technical buyers, long evaluation cycles, security/compliance requirements

GTM Motion: Likely enterprise sales with marketing supporting pipeline generation

Marketing Ops Reality

What "AI & Automation" Means Here:

• This is a NEW role specifically created for AI/automation focus
• You're not inheriting a mature AI program - you're building it
• Expect a lot of "let's test this tool and see if it's useful"
• Some will work, most won't - that's the job

Your Tech Stack (Likely):

• Marketo (confirmed - your boss is a 6x Champion)
• Salesforce or similar CRM
• Various point solutions for webinars, events, ABM, attribution
• You'll be evaluating/implementing new AI tools

Cross-Functional Dependencies:

• Sales ops team (data hygiene, lead routing, reporting)
• Demand gen (campaign automation, lead scoring)
• Field marketing (event automation, follow-up workflows)
• Product marketing (content delivery, personalization)

What You'll Actually Do

Time Breakdown

Automation Builds (40%) | AI Tool Testing (30%) | System Admin (30%)

Key Activities

• Build Campaign Automation: Design and configure email nurture flows, webinar follow-up sequences, event automation in Marketo. Debug when something breaks (which is often). Optimize open rates, click rates, conversion rates.

• Evaluate AI Tools: Test new AI platforms for use cases like email copy generation, lead scoring, intent data analysis, chatbot optimization. Most won't be worth it. Document what works, kill what doesn't.

• Integrate Systems: Build or fix connections between Marketo, CRM, data warehouse, event platforms, ABM tools. Write API calls when vendor integrations don't exist. Clean up data mapping errors.

• Optimize Lead Routing: Configure lead assignment rules, scoring models, routing logic. Deal with sales ops when leads go to the wrong rep. Adjust when territories change or rules break.

• Report on Performance: Build dashboards showing campaign performance, funnel metrics, attribution data. Troubleshoot when numbers don't match between systems (they often don't).

The Honest Reality

What's Hard

• "AI" is mostly hype right now: You'll test a lot of tools that claim AI capabilities but are just glorified rules engines. Your job is to find the 10% that actually add value.

• Data is always messy: Duplicate records, missing fields, bad imports, salespeople overwriting automation. You spend a lot of time cleaning up data problems you didn't create.

• Cross-team dependencies: You need sales ops to fix CRM issues, IT to grant API access, demand gen to clarify requirements. Projects take longer than they should because you're waiting on other people.

• Vendor overpromises: Marketing automation vendors sell you features that don't work as advertised. You'll spend time working around platform limitations.

• Ambiguity on new role: This role is new - priorities might shift as leadership figures out what "AI in marketing ops" actually means for them.

What Success Looks Like

• Automation ROI: You build workflows that save the marketing team 10-20 hours per week on manual tasks

• Campaign Performance: Email and nurture metrics improve (higher open rates, better conversions, fewer unsubscribes)

• AI Wins: You implement 2-3 AI tools that demonstrably work - generating better copy, improving lead scoring, or surfacing better insights

• System Reliability: Lead routing works correctly, data syncs between systems, campaigns fire on schedule

• Stakeholder Trust: Marketing and sales teams come to you first when they need automation or want to test new tools

Who You Work With

Internal Stakeholders:

• Marketing Ops Leader (your boss): Extremely technical, knows Marketo deeply, will give you autonomy but expects high-quality work
• Demand Gen Team: Your primary customer - they need campaign automation, lead scoring, reporting
• Sales Ops: You'll partner on CRM issues, lead routing, data quality
• Field Marketing: Event automation, follow-up workflows, regional campaign support

What They Care About:

• Speed: Can you build this automation quickly?
• Reliability: Will it actually work or break in production?
• Data: Are the numbers accurate and consistent across systems?
• Results: Did campaign performance improve after your changes?

Requirements

• Deep marketing automation experience: You've built complex workflows in Marketo, HubSpot, Pardot, or similar. You know how to debug when automation breaks.

• Technical comfort: You can read API documentation, write basic scripts, troubleshoot integration errors. You're not a developer but you're not afraid of code.

• AI curiosity: You're genuinely interested in testing AI tools for marketing use cases. You know most will fail but you like experimenting.

• Data hygiene discipline: You understand data models, normalization, deduplication. You care about clean data.

• Cross-functional communication: You can translate technical concepts for non-technical marketers and explain marketing requirements to technical teams.

• Self-direction: This is a new role - you need to figure out priorities, propose projects, and drive initiatives without someone telling you exactly what to do.

• Realistic about hype: You can separate AI vendor marketing from actual capabilities. You're skeptical by default and test thoroughly before recommending tools.