GTM Engineer

Technical Skills

Proven ability to build and deploy automation and integration solutions across enterprise GTM tech stacks, with hands-on Salesforce (CRM) experience — including custom objects, flows, APIs, and data management.

JavaScript development capability sufficient to build lightweight applications, custom integrations, and browser-based tooling that solves real GTM workflow problems.

Experience querying Amazon Redshift or a comparable cloud data warehouse to extract, transform, and surface data that powers automation logic and sales insights.

Ability to design and ship AI-powered workflows using modern large language model (LLM) APIs — particularly Anthropic’s Claude — including prompt design, tool use, and reliable production deployment.

Enough understanding of sales and customer success processes to independently identify root causes of workflow friction and scope solutions without heavy business analyst support.

Behavioural Skills

Walks into ambiguous situations and finds the real problem — listens carefully to what salespeople say is slowing them down, then digs to understand what’s actually causing it, and comes back with a clear proposal rather than more questions.

Builds for the person using it, not for themselves — measures success by whether salespeople actually adopt and rely on what they’ve built, not by the technical elegance of the solution.

Bias for action — ships working prototypes quickly, puts them in front of real users, and iterates based on feedback rather than over-engineering before launch.

Comfortable working across technical and non-technical boundaries — can discuss API design with an engineer in the morning and explain the same solution to a sales rep in the afternoon.

Curious and self-directed — actively explores new tools, models, and automation techniques, and brings ideas to the table without waiting to be pointed at the next problem.

AI Skills

Uses AI tools — including Claude — as a core part of their own development workflow, not just as a writing aid.

Can design, build, and ship production-quality AI-powered automations and features, with a working understanding of prompt engineering, context management, and failure modes in LLM-based systems.

Proactively identifies where AI can replace or augment manual GTM workflows, and builds the business case for adoption based on real usage data.