GTM AI Engineer

NetBrain

10h•$160,000 - $190,000

About The Position

Founded in 2004, NetBrain is the leader in no-code network automation. Its ground-breaking Next-Gen platform provides IT operations teams with the ability to scale their hybrid multi-cloud connected networks by automating the processes associated with Diagnostic Troubleshooting, Outage Prevention and Protected Change Management. Today, over 2,500 of the world’s largest enterprises and managed services providers leverage NetBrain’s platform. We are hiring an AI GTM Engineer to accelerate AI adoption across NetBrain's go-to-market function. This is a builder role — you will wire together LLMs, build custom GPTs, automate high-toil GTM workflows, and create tools that let a team of 20 operate like a team of 40. You will sit within Marketing Operations and work closely with Marketing, Sales, and Customer Success. You are not a consultant who recommends tools for others to implement. You build things, deploy them, train the people who use them, measure the impact, and iterate. The work is hands-on, the mandate is real, and the visibility is high. This role is part of how NetBrain demonstrates credibility with customers pursuing Agentic NetOps: we model the behavior we advocate. You will be a key driver in how we imagine a new way of working for the Marketing organization and the broader GTM strategy.

Requirements

You have hands-on experience building AI applications or working with LLMs in production environments — not just prompting, but deploying.
You are a builder first. You ship imperfect things, learn, and improve. You do not spend months in requirements before writing a line of code
You understand marketing and sales processes — you can identify where AI adds value because you understand the underlying workflow, not just the technology
You are fluent with LLM APIs (OpenAI, Anthropic, or equivalents), prompt engineering, and AI application architecture as well as emerging technology (e.g. OpenClaw)
You pick the right tool: no-code when speed matters, code when complexity demands it
You can communicate AI capabilities to non-technical stakeholders — you make the work accessible, not intimidating
You are genuinely frustrated by how slowly most organizations adopt AI and you want to be somewhere that moves at a different pace
You have enough commercial intuition to prioritize use cases by GTM impact, not just technical interest
Manual Dexterity: Repetitive motion of wrists, hands and fingers for using a computer.
Stationary Tasks: Sitting for extended periods, remaining in a stationary position.

Responsibilities

Build and deploy custom GPTs and AI assistants that make marketing and sales workflows faster — battlecard generation, proposal drafting, email personalization, customer research, meeting prep
Create and maintain a prompt library: reusable, tested prompts the team can apply without needing to engineer from scratch
Train team members on effective AI use; make the tools accessible enough that adoption is not a barrier
Map the GTM function for high-toil, repeatable work — and empower the team AI & automation
Target: lead enrichment, content personalization, campaign reporting, data hygiene, and pre-meeting intelligence packages
Use the right tool for the job — no-code/low-code (Make, Zapier, n8n) for fast deployment, API/code for complex integrations
Build AI-assisted workflows that compress first-draft content creation — blog posts from call transcripts, social from blog, email sequences from campaign briefs etc.
Explore and prototype AI-powered buyer enablement tools — chatbots, qualification flows, dynamic demo experiences.
Work with the website rebuild team to identify where AI interaction can improve the buyer journey and reduce time to qualified conversation.
Continuously evaluate emerging AI tools for GTM applicability — help NetBrain stay ahead of the market.
Recommend and implement new capabilities with a clear ROI thesis; deprecate what is not driving measurable output.
Ensure AI tools integrate with the broader marketing and sales tech stack (CRM, marketing automation, analytics)
Measure what matters: time saved, output volume, quality improvement, pipeline influence — not tools deployed.
Report AI adoption and impact to the Sr. Director of Marketing Operations and CMO on a regular cadence.
Build the internal business case for continued AI investment based on demonstrated results.