Description
Neo Security is hiring a GTM Engineer to sit at the intersection of revenue marketing and AI-powered engineering. This is a hands-on, builder-focused role: you'll design and ship the automations, agents, and data workflows that make our marketing and revenue engine faster, smarter, and more personalized than what off-the-shelf tools alone can do. You'll spend your time equally between wiring up best-in-class AI and marketing tools and writing the scripts, prompts, and lightweight applications that connect them, fill their gaps, and push them further than out-of-the-box functionality allows.
As an AI-native security company, we expect our own marketing function to reflect the same edge we sell to customers. This role suits someone who is part growth marketer, part technical builder — comfortable in a spreadsheet, an API playground, and an LLM prompt window in the same afternoon, and who gets genuine energy from finding the newest AI tool or technique before most of the market has heard of it.
What You'll Do
- Design, build, and maintain AI-powered workflows and automations across the revenue funnel — lead scoring and enrichment, intent signal aggregation, personalized outbound, and lifecycle nurture.
- Build custom internal tools, scripts, and lightweight agents (using LLM APIs, no-code/low-code platforms, and traditional code) to close gaps between off-the-shelf marketing and sales tools.
- Evaluate, pilot, and integrate bleeding-edge AI tools and platforms into the GTM stack, moving quickly from experimentation to production where it delivers real results.
- Own integrations across the marketing and sales tech stack (CRM, marketing automation, data warehouse, enrichment/intent providers), ensuring clean, connected data flows.
- Partner with Demand Generation, Field Marketing, and Sales to identify high-leverage opportunities where automation and AI can increase pipeline, personalization, or team efficiency.
- Build and maintain AI-assisted content and campaign workflows (e.g., dynamic personalization at scale, automated research/briefing for outbound, AI-assisted creative variants) in partnership with content and campaign owners.
- Prototype quickly, measure impact rigorously, and kill or scale experiments based on results rather than novelty.
- Maintain documentation and internal enablement so non-technical marketing and sales teammates can use the tools and workflows you build.
- Monitor the reliability, cost, and performance of AI-powered systems in production, iterating as models and tools evolve.
- Stay deeply plugged into the AI tooling landscape (new models, agent frameworks, GTM-specific AI products) and bring relevant innovations back to the team.
Requirements
- 3+ years of experience in a technical marketing, growth engineering, marketing operations, or GTM engineering role, ideally at a B2B SaaS or AI company.
- Hands-on coding ability (e.g., Python, JavaScript) sufficient to build scripts, automations, and lightweight tools/integrations independently.
- Practical experience building with LLM APIs (e.g., OpenAI, Anthropic) and/or AI agent frameworks, beyond just using off-the-shelf AI features.
- Strong working knowledge of the modern marketing/RevOps stack (CRM, marketing automation, data warehouse, enrichment and intent data tools) and how to integrate them via APIs or iPaaS tools (e.g., Zapier, Make, Workato).
- A demand generation or growth marketing mindset — comfortable thinking in terms of pipeline, conversion, and funnel metrics, not just tooling for its own sake.
- Strong bias toward rapid prototyping and iteration, with good judgment about when to build versus buy versus stop.
- Excellent cross-functional communication skills, able to translate technical builds into business impact for marketing and sales stakeholders.
- Genuine enthusiasm for staying current on cutting-edge AI tools, techniques, and platforms.
- Based in the United States, able to work remotely across U.S. time zones.
Nice to Haves
- Experience building AI agents or multi-step automated workflows for sales/marketing use cases (e.g., automated account research, AI SDR-style outbound, dynamic content generation).
- Experience with data pipelines and warehousing (e.g., SQL, dbt, Snowflake/BigQuery) to support more advanced reporting and personalization use cases.
- Prior experience in a startup environment building GTM systems and tools from scratch rather than working within an established stack.
- Familiarity with ABM and intent data platforms (e.g., 6sense, Demandbase, Clay) and how to extend or combine them with custom tooling.
- Experience in cybersecurity or another technical, security-conscious industry.
- A public presence or portfolio (e.g., blog, GitHub, case studies) demonstrating GTM/AI builds you've shipped.
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