GTM Engineer
Build and deploy AI agents and automated workflows that power marketing execution, programmatic outbound, and pipeline generation at scale. Requires CS background, hands-on LLM/agent experience, and GTM intuition.
AI Automation Engineer (GTM)
Builds AI-powered automation pipelines and vector database infrastructure for GTM systems, integrating with marketing/sales tools like HubSpot and Clay. Requires strong Python, production RAG/vector DB experience, and GTM context knowledge.
140k – 180kMarina del Rey, CASan Francisco, CAGTM EngineeringHybrid
About the role
Responsibilities
- Architect and build AI-powered GTM systems: design and ship automation pipelines across outreach, competitive intel, sales enablement, inbound, events, content, and reporting.
- Write and maintain production code: build Python scripts, APIs, integrations, vector database infrastructure (ingestion pipelines, embedding models, retrieval logic). Push to GitHub and document.
- Lead AI workflow development: translate ideas into systems, decide on AI models, rules, or alternatives; ensure reliable production output.
- Build and own knowledge infrastructure: design vector database, ingestion pipelines, chunking strategies, embedding models, retrieval logic.
- Contribute to GTM tech stack: manage integrations with Slack, HubSpot, Clay, and other tools.
- Collaborate with marketing, sales, ops; identify bottlenecks and ship solutions.
- Drive AI roadmap: prioritize, sequence builds, surface tradeoffs.
- Maintain and improve shipped systems: monitor performance, handle failures.
Requirements
- Strong Python skills: build, debug, own scripts/pipelines, APIs, data manipulation, GitHub.
- Vector database experience: embedding-based retrieval, RAG pipelines, chunking, embedding models, evaluation (Pinecone, Weaviate, pgvector, etc.).
- Shipped real automation: systems with inputs/outputs, failure handling.
- Production AI experience: prompt engineering, API integration, output validation.
- GTM context knowledge: BDR needs, sales cycles, enablement.
- Self-sufficient: prototype from vague ideas.
- Work well with non-technical teams; curious about AI tooling.
Compensation
Salary: $140,000 - $180,000 per year, plus bonus, equity, benefits.
Skills
PythonVector DatabasesRAGPineconeWeaviatePgvectorPrompt EngineeringAPIsGitHubHubSpotSlackClay
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