GTM AI Engineer

Buildots

. Identify high-value opportunities for AI across the go-to-market lifecycle .

Posted 9/17/2026full-timeTel Aviv • IsraelMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and implementing AI agents and workflows across the go-to-market lifecycle, with a strong focus on integrating AI solutions into existing systems and measuring their business impact. Proficient in collaborating with cross-functional teams to ensure secure, maintainable, and scalable AI applications.

Highest-signal resume keywords

AI Agent DevelopmentCloud-Based Services DeploymentREST API IntegrationData Warehouse ManagementAI Impact Measurement

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

AI Workflow DesignLLM DevelopmentAPI IntegrationSQLCI/CDMonitoringObservabilityTool UseContext ManagementAgent Frameworks

Soft Skills

CommunicationCollaborationCommercial CuriosityJudgmentDecision-Making

Tools & Technologies

SalesforceSlack ApplicationsGTM ToolsData Connectivity ToolsAutomation Tools

Industry Keywords

Go-To-Market LifecycleRevenue OperationsBusiness ApplicationsLead ManagementPipeline Management

Tech Stack

Tools & technologies

CloudSQL

About the role

Key responsibilities & impact

Identify high-value opportunities for AI across the go-to-market lifecycle
Design and ship AI agents, automations, and AI-powered workflows for prospecting, enrichment, lead management, account planning, deal support, approvals, pipeline management, forecasting, call intelligence, and expansion
Turn internal prototypes into reliable production services used across the organization
Collaborate with Engineering and DevOps to ensure solutions are secure, maintainable, and scalable
Define where AI can act independently and where humans remain in the loop
Build evaluation, monitoring, permissions, and auditability for agents interacting with commercial systems and data
Work across CRM, GTM tools, and data warehouse systems to improve data connectivity, structure, and availability
Measure business impact through cycle times, data quality, productivity, conversion, and time returned to teams
Communicate AI impact clearly to the business
Create patterns, tooling, and standards that enable others to build safely and effectively
Help the organization discover, trust, and use AI capabilities
Work across Sales, Solutions, Customer Success, Marketing, and Revenue Operations

Requirements

What you’ll need

3–7 years of relevant experience in roles such as GTM Engineer, AI GTM Engineer, RevOps Engineer, Business Applications Engineer, Solutions/Sales Engineer with a strong technical background, AI-forward Salesforce Developer, or Forward Deployed Engineer
Strong engineering ability; ability to take an idea from prototype to working production system, integrate with APIs and existing applications, and make pragmatic technical decisions
Hands-on experience building with LLMs and agents, including tool use, structured workflows, context management, retrieval, agent frameworks, or similar approaches
Understanding of how to evaluate whether AI systems work reliably
Comfort deploying and operating cloud-based services
Knowledge of authentication, permissions, CI/CD, secrets, monitoring, and observability
Experience with REST APIs, webhooks, OAuth, Slack applications, SQL, and data warehouses
Good judgment about AI autonomy and designing systems appropriately when AI interacts with important business processes
Commercial curiosity and ability to connect automation to measurable business outcomes
Ability to explain technical choices clearly, work across functions, and build confidence in new ways of working
Ability to learn quickly and make good decisions in an environment where the playbook is still being written