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GTM AI Engineer
Not specifiedFull-timeAI EngineeringConstruction
Build production-grade AI agents, automations, and workflows that improve go-to-market operations across sales, solutions, customer success, marketing, and revenue operations.
Responsibilities
- Design and deploy AI agents, automations, and workflows across prospecting, enrichment, lead management, account planning, deal support, approvals, pipeline management, forecasting, call intelligence, and expansion.
- Turn internal AI experiments into reliable, secure, maintainable, and scalable production services.
- Define appropriate boundaries for AI autonomy and implement evaluation, monitoring, permissions, and auditability.
- Improve the connections and structure of data across CRM systems, go-to-market tools, and data warehouses.
- Measure the business impact of AI initiatives through cycle time, data quality, productivity, conversion, and time-saved outcomes.
- Create patterns, tools, and standards that enable other teams to build and use AI safely and effectively.
- Partner with engineering and DevOps teams to operate production AI services.
Requirements
- 3–7 years of relevant experience in GTM engineering, AI engineering, revenue operations engineering, business applications engineering, technical sales or solutions engineering, Salesforce development, or forward-deployed engineering.
- Strong engineering skills, including the ability to turn prototypes into production systems and integrate APIs with existing applications.
- Hands-on experience building LLM- and agent-based systems using tool use, structured workflows, context management, retrieval, agent frameworks, or similar methods.
- Experience deploying and operating cloud services, including authentication, permissions, CI/CD, secrets management, monitoring, and observability.
- Experience with REST APIs, webhooks, OAuth, Slack applications, SQL, and data warehouses.
- Ability to design appropriate levels of AI autonomy, including human review, evaluation, permissions, and auditability.
- Commercial judgment and the ability to connect automation opportunities with measurable business outcomes.
- Ability to explain technical decisions clearly, collaborate across functions, and build confidence in new working practices.