Full-Stack Engineer, AI Native GTM Systems
New
Remote, U.S.-basedFull-TimeMiddle
Salary not disclosed
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Job Details
- Required Skills
- Node.jsPythonSQLSalesforceTypeScriptReactHubSpot
Requirements
- Strong full-stack engineering ability with experience shipping production applications end to end
- Experience building modern applications with tools such as TypeScript, React, Node.js, Python, and SQL
- Strong system design skills and good judgment around architecture, maintainability, and tradeoffs
- Experience building AI-native products, agentic systems, or intelligent workflows that go beyond simple prompt wrappers
- Familiarity with frameworks and tooling such as AI-SDK, LangGraph, Agno, or similar orchestration patterns
- Strong product sense and the ability to turn ambiguous business needs into usable software
- Experience working with APIs, integrations, authentication, and event-driven or workflow-based systems
- Comfort working directly with internal stakeholders and owning delivery with minimal oversight
- High velocity with AI-assisted development tools such as Cursor, Claude Code, Codex, or custom engineering harnesses
- Experience building software for GTM, operations, or other internal business teams (preferred)
- Experience with systems such as Salesforce, HubSpot, and modern GTM tooling (preferred)
- Experience with data workflows, analytics systems, and operational reporting (preferred)
- Background in B2B SaaS, cybersecurity, or technical product environments (preferred)
- Familiarity with enrichment providers, workflow orchestration, and modern GTM infrastructure (preferred)
Responsibilities
- Build internal applications that improve execution across GTM, operations, and customer-facing teams
- Design and ship AI-native products, agentic workflows, and full-stack systems end to end
- Develop integrations across Salesforce, HubSpot, product data, and other business systems
- Build AI-assisted and agentic workflows that improve speed, decision quality, and execution
- Build reliable data flows, orchestration layers, and system architecture that scale with the business
- Partner with business stakeholders to identify high-value problems and ship practical solutions quickly
- Use modern AI development tools and engineering workflows to accelerate delivery without compromising quality
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