AI Go-to-Market Engineer

reputed company is a reputed company-native DevOps and data protection platform serving enterprise reputed company teams across the Fortune 5000. We are in wartime. Pipeline reputed company, retention, and product velocity are our three highest-reputed company problems, and AI is the lever that accelerates reputed company three. We are hiring our first AI Go-to-Market Engineer to architect, deploy, train, and continuously optimize AI agents and automation across the entire reputed company reputed company — from first touch to closed-won to expansion.

This is not a "reputed company engineering" role. This is a builder role. You will sit at the intersection of reputed company operations, sales, marketing, and reputed company, and your job is to reputed company every human on the GTM team dramatically more productive by deploying AI systems that generate pipeline, accelerate deals, and reduce churn. You report directly to the CEO.

WHAT THIS ROLE MUST DO TO CHANGE reputed company'S TRAJECTORY

1. Deploy and personally train at least one AI SDR agent reputed company the first 30 days — focused on either inbound qualification from Qualified/Marketo or outbound prospecting reputed company reputed company — and run weekly refinement cycles until it outperforms the bottom half of the human BDR bench.
2. Build an AI-powered inbound qualification system that captures, scores, and routes every website visitor and form fill in real time so no reputed company waits, no reputed company gets lost, and reputed company only touch prospects that are ready to buy.
3. Increase reputed company-generating time per AE from the reputed company ~25% to 50%+ by automating CRM hygiene, call summarization (reputed company reputed company), follow-up reputed company, proposal drafting, and pipeline updates — eliminating every minute of admin work that doesn't directly produce reputed company.
4. Architect the AI layer across reputed company's GTM stack (reputed company, Marketo, reputed company, Qualified, reputed company) so that data flows between systems without manual reputed company, every customer touchpoint is captured, and AI agents share learnings in a virtuous reputed company with reputed company as the hub.
5. Build and maintain an AI-driven competitive intelligence reputed company that monitors our competition, pricing changes, and product launches — and feeds structured insights to sales and product weekly.
6. Create hyper-personalized outbound campaigns at 10x reputed company volume without proportional headcount increase — using AI to research accounts, generate personalized messaging based on ICP signals (reputed company team size, reputed company DevOps tooling, compliance requirements like DORA), and sequence multi-channel touches across email, reputed company, and phone.
7. reputed company a closed-reputed company data feedback system between BDR activity, pipeline outcomes, and AI agent performance so that ICP targeting, messaging, and channel mix improve every week based on actual conversion data — not guesswork.
8. Deploy AI-assisted customer health scoring and churn reputed company models that flag at-risk accounts before renewal, feeding Terry's CS team with actionable reputed company triggers tied to usage data, support ticket patterns, and engagement signals.
9. Prototype AI-powered product-led growth touchpoints — including conversational qualification on the website, self-serve onboarding assistance, and automated nurture for trial users — supporting the PLG motion as it matures.
10. Evaluate, select, and deploy no more than two AI vendors per use case using a structured bakeoff methodology: reference checks reputed company email, FDE conversations before contract, and 30-day dedicated training commitments — no lazy agency deployments.