The Lead GTM Engineer designs, builds, and leads the AI and data systems that power Weave's go-to-market engine. This is a hands-on technical leadership role on the GTM AI Taskforce: you'll architect agentic AI workflows and the data infrastructure beneath them, spanning lead distribution, enrichment, scoring, and sales-conversation intelligence, while mentoring the engineers and analysts who build alongside you. You'll set the technical standards for how Weave applies LLMs and modern data tooling to revenue problems, and act as the connective layer between Revenue Operations, Sales, Marketing, and Business Intelligence. This role suits a builder-leader who's equally comfortable writing SQL and Python as they are mentoring a teammate or evaluating a vendor.
- This position will be hybrid (3 days/week at Weave HQ)
- Reports to: Director, Revenue & GTM Operations
What You Will Own- Lead the technical initiatives. Own AI-GTM technical initiatives end to end, from roadmap through production, as the technical lead accountable for outcomes.
- Set the technical bar. Define standards for code quality, data quality, evaluation, and deployment; review designs and mentor the engineers and analysts contributing to the work.
- Serve as the quality gate. Act as the technical QA checkpoint on GTM AI projects before they ship, and steward shared infrastructure like repository access and connector credentials.
- Architect agentic workflows. Design multi-step, tool-using agents that autonomously execute GTM tasks, for example a self-optimizing lead-distribution agent that sets caps, routes leads in real time, and refines its own logic from closed-lost analysis.
- Build the data foundation. Design and maintain the pipelines, canonical data models, and golden-record schema in Snowflake and BigQuery that every downstream GTM AI project depends on.
- Own evaluation and reliability. Build eval harnesses and guardrails, measure accuracy and drift, and manage cost, latency, and version control for everything you ship.
- Integrate systems. Connect Salesforce, enrichment vendors, and other source systems via APIs and MCP-based integrations, owning ingestion, deduplication, and match logic.
- Lead vendor evaluation. Own technical proofs of concept and due diligence for data and AI vendors, from benchmarking through production integration.
What You Will Need to Accomplish the Job- Bachelor's degree in Engineering, Computer Science, Data, or a related field, or equivalent hands-on experience building production data and AI systems.
- Advanced SQL and working proficiency in Python.
- Hands-on experience with Snowflake and BigQuery.
- Demonstrated experience building AI agents with tools such as Claude, Claude Code, or Gemini.
- Experience taking technical projects from concept through production rollout.
- A track record of mentoring or reviewing the work of other engineers or analysts.
What Will Make Us Love YouPreferred qualifications - including personality traits and soft skills.
- You've built or evaluated agentic frameworks and applied LLM evaluation at scale.
- You have experience with Snowflake Cortex, dbt, or Salesforce Agentforce.
- You've owned vendor evaluation and integration end to end.
- You've led or helped build a data, AI, or GTM-engineering function.
- You have experience in a GTM, Revenue Operations, or sales-analytics environment.
