GTM Engineer - ABM, Advertising and Growth Marketing

WHAT YOU'LL DO:

• Streamline and optimize digital marketing, ABM, and growth marketing processes, including advertising campaign creation, audience segmentation, and offline workflows that enable boutique customer touchpoints at scale.
• Serve as the primary technical partner to the internal Paid Media & ABM team, co-developing the innovation roadmap, fast-tracking automation priorities, and translating their strategic needs into production-ready AI solutions.
• Partner with cross-functional, global Marketing teams and Data and Analytics to identify and scope opportunities for AI-driven solutions and technology adoption across teams.
• Integrate AI APIs, MCP Servers, and other automation tools to build agents and workflows that improve Marketing’s paid media and abm motions at scale.
• Design and maintain Workato-based automation recipes and integrations that orchestrate lead routing, audience activation, and campaign operations across the GTM stack; integrate AI APIs and MCP Servers to build intelligent agents that accelerate ABM and paid media workflows.
• Architect, build, and deploy AI prototypes and scalable automated workflows (integrating LLMs and AI APIs) to proactively eliminate friction and drive efficiency gains across end-to-end marketing processes.
• Design and build first- and third-party data-driven feedback loops that connect ad platform data, first-party campaign responses, and down-funnel pipeline metrics into a unified closed-loop system — including integration with offline conversion APIs to enable value-based bidding strategies that optimize ad spend toward pipeline and revenue.
• Run structured experiments to evaluate AI tools, prompt strategies, and automation approaches - rapidly iterating from proof-of-concept to production.
• Create and maintain technical documentation and training materials to ensure adherence to operational best practices and increase team self-sufficiency.
• Build and manage CDP-driven audience pipelines — configuring audience syncs, match rate optimization, and suppression workflows to ensure paid media campaigns target the right accounts with minimal waste.
• Build and enforce outcome-specific campaign setup frameworks, accounting for differentiated requirements and KPIs across Paid Media and ABM
• Define and track KPIs that measure the impact of AI and automation investments - including time savings, workflow efficiency gains, audience match rates and contribution to pipeline from AI-enhanced campaigns.

OUR IDEAL CANDIDATE WILL HAVE:

• 4+ years of demonstrated experience in Marketing Operations or Revenue Operations within a high-growth SaaS environment.
• Hands-on, expert-level experience with advertising solutions including LinkedIn, Google, Meta, Reddit, Influ2, Demandbase and industry-leading DSP’s.
• Expert-level, hands-on experience with Workato (required) — building and maintaining recipes, API connectors, and error handling for marketing automation workflows. Experience with Clay or similar enrichment tools is a plus.
• A proven track record of applying AI or advanced automation to solve complex business problems, with practical experience with AI concepts (LLMs, RAG, prompt engineering).
• Strong proficiency in Python or JavaScript/TypeScript for building automation scripts and handling API requests.
• Experience evaluating and adopting emerging AI tools (e.g., new LLM capabilities, AI-native marketing platforms).
• Exceptional communication and executive presence, with the ability to clearly articulate complex technical strategies to both technical and non-technical stakeholders.
• A "builder" and "practical innovator" mindset: who turns problems into scalable solutions.
• Highly analytical and process-driven, focused on efficiency and scalability.
• Proficiency in SQL, or BI visualization tools (e.g., Tableau, Looker, Power BI) is a definite advantage.
• Experience building and managing CDP-driven audience pipelines, including audience syncs, match rate optimization and suppression workflows.
• Familiarity with agent frameworks (e.g., LangChain, CrewAI, or similar) for building multi-step AI workflows is a plus.