GTM Engineer - Sales Workflow Automation, Revenue Intelligence

Responsibilities

• Agentic workflows that automate high-volume sales work end to end: follow-up drafting, deal stage updates, task creation, and Slack and CRM notifications, with approval gates and handoffs that keep reps in control.
• Integrations between our prospecting agents and adjacent systems (quoting, pricing, case creation) so a rep can go from signal to action without leaving their workflow.
• Pipelines that pull conversation intelligence transcripts into Snowflake and the CRM, and services on top of them that produce next best actions, deal risk flags, and coaching recommendations for frontline managers.
• The production controls around all of it: evals that catch regressions before reps see them, observability tied to pipeline and revenue outcomes, permissions and sensitive-data handling, error recovery and rollback.
• A third-party signal layer (intent, news, firmographic change) that flows into account prioritization, and the win/loss data capture that tells us what's working.
• What you'll need to thrive (Requirements)
• Proficiency in Python (TypeScript also works) and strong SQL. You write production-grade, tested code, and you can read, modify, and debug code you didn't write, including code generated by AI tools.
• At least one LLM-powered workflow or agent you built that a business team used in production, built against an LLM API (Anthropic, OpenAI, or similar) or an agent framework (LangGraph, Claude Agent SDK, or similar), with tool calling, error handling, and some form of evaluation. You'll be asked to walk through it.
• Hands-on Salesforce experience: data model, Flow, APIs, permissions, and what happens when an integration writes bad data at scale.
• Comfort working directly in a data warehouse (Snowflake preferred) for pipeline QA, transformation, and validation.

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