Senior Marketing Operations Manager

Ambient.ai is the category creator and leader in Agentic Physical Security. Powered by Ambient Pulsar, the first reasoning Vision-Language Model purpose-built for physical security, our platform seamlessly integrates with existing security cameras and physical access control systems to unify monitoring, access control, threat assessment, response, and investigations through an always-on reasoning layer that augments security operators with superhuman capabilities. The results: 95% fewer false alarms, investigations 20x faster, and 10x faster response.

The momentum speaks for itself: we doubled new ARR in FY26, we process 200M+ video hours per day, and have delivered results for world-class customers including Cisco, ServiceNow, SentinelOne, TikTok, Bayer, and MoMA. That kind of momentum creates an environment where great people thrive, and it shows: we recently ranked #71 out of 500 on the Forbes best startup employers list.

Founded in 2017 and backed by Andreessen Horowitz, Y Combinator, and Allegion Ventures, Ambient.ai is on a fast-paced journey to fulfill our mission: prevent every security incident possible.

Ready to learn more? Connect with us on LinkedIn and YouTube

In this role, you’ll own the marketing tech stack, the data, and the systems that turn campaigns into a pipeline. This is a hands-on, builder role — equal parts operator, architect, and AI engineer.

You’ll be the connective tissue between marketing, sales, RevOps, and BDR. If our attribution model is wrong, our lead routing breaks, our MQL-to-S1 conversion drops, or a campaign launches without proper UTM hygiene — that’s your problem to solve. If we want to scale 10x without adding headcount, you’re the one architecting the agents and automations that make it possible.

• HubSpot as our marketing automation platform — workflows, lifecycle stages, lead scoring, list hygiene, form architecture, integrations

• Salesforce sync, field mapping, and shared data model with RevOps

• Lead routing logic and SLA enforcement across BDR and AE teams

• MAP/CRM governance — who has access to what, audit trails, data retention

• Multi-touch attribution model — what touches we credit, how we weight them, how we reconcile self-reported vs. tracked source

• Source-of-truth dashboards for MQLs, S1s, S2s, CPL, ROAS, pipeline contribution by program

• Weekly and quarterly reporting cadence — pacing against goal, channel-level performance, deal velocity by source

• Marketing P&L hygiene — budget vs. actuals by program, partnership with Finance on accruals

• Build and maintain the marketing AI agent stack (Claude, MCP servers, n8n, Supabase)

• Operationalize agents for influencer signal detection, content generation, competitive intel, and weekly recaps.

• Knowledge base infrastructure — how marketing context, brand assets, and historical campaign data are stored, retrieved, and used by agents.

• Partner with GTM Engineering on intent signal layering and Revenue Intel integrations

• Sales partnership — work with RevOps on shared definitions (what’s an MQL, what’s an S1, what makes a lead enrichable)

• BDR enablement — make sure they get the right leads with the right context at the right time

• Vendor management for the martech stack

• 6+ years in marketing operations at a B2B enterprise software or SaaS company

• Deep HubSpot expertise — you’ve architected lifecycle stages, built workflows from scratch, and debugged the weird ones

• Salesforce fluency — you can read a flow, write a SOQL query, and explain why a lead didn’t route

• Hands-on with a paid media platform (Metadata, 6sense, Demandbase, or similar ABM tooling)

• Comfort with attribution complexity — you know first-touch vs. last-touch vs. W-shaped, and you have an opinion on which is right for which question

• SQL or comfort in BI tools (Looker, Tableau, Hex, or similar)

• Experience operationalizing AI tools in a marketing workflow — not just experimenting, but shipping into production

• Strong written communication, you can document a process so the next person can run it.

• Experience with Clay, n8n, Supabase, or other agent infrastructure

• You’ve built or contributed to an MCP server, a Claude project, or a custom AI agent

• Background in physical security, IoT, or enterprise infrastructure software

• You’ve worked closely with a BDR team and know what good lead routing actually looks like.

• Python or TypeScript proficiency