Revenue Programs & AI Enablement Manager

What you'll do

• Design and operate multi-agent systems connecting Salesforce, Gong, Slack, Snowflake, and proprietary TV data into unified, real-time GTM workflows
• Build and maintain MCP servers to provide Claude governed, real-time access to GTM stack including live Salesforce records, Gong call data, and Samba viewership signals
• Automate aggregation, summarization, and routing of deal intelligence across tools to eliminate manual data transfer and context-switching for sellers
• Create RAG pipelines and prompt libraries to give Claude accurate, governed context on products, prospects, pricing, and competitive landscape
• Architect integrations between AI services and internal systems using Python and APIs, enriching contact and account records with live signals
• Design and run structured evals across all production AI systems to measure output quality, accuracy, regression risk, and real business impact
• Build eval frameworks to catch prompt drift, model behavior changes, and degraded tool use before impacting sellers
• Run A/B experiments across workflows to prove impact on pipeline and revenue
• Monitor agentic systems in production and own feedback loop for issues and fixes
• Serve as internal authority on Claude across Revenue Org: best practices, MCP architecture, prompt engineering standards, and enablement
• Write documentation and run enablement sessions to help sellers and operators extract value from systems
• Build systems that surface deal risk, flag renewal exposure, draft personalized outreach, and score accounts by conversion likelihood using real viewership signals
• Connect Gong call intelligence, Salesforce pipeline data, and Samba TV audience signals into unified account views for sellers
• Design workflow automation to reduce cognitive load on sellers, allowing more time selling and less time on CRM updates and repetitive tasks
• Identify and eliminate highest-friction points in GTM process through automation

Requirements

• 3 to 5 years in software engineering, data engineering, or GTM/revenue operations engineering with serious technical depth
• Owned an AI or automation function, not just contributed to one
• Production-level Python and/or JavaScript; write, ship, and maintain code others depend on
• Hands-on LLM production experience: prompt engineering, tool use, multi-turn agentic workflows, RAG
• Experience building and operating MCP servers that connect LLMs to live business systems and data sources
• Knowledge of eval practices: measure AI system performance, build regression tests, catch drift before issues
• Deep, production-level Claude expertise including API, structured outputs, tool use, agentic workflows, system prompt design; ability to teach and build reliable systems
• Hands-on experience with Claude Code as primary development environment
• Salesforce hands-on experience (SOQL, APIs, Flows) plus at least one sales engagement platform, preferably Gong
• Snowflake and dbt working knowledge for querying and transforming data to support AI workflows
• Genuine understanding of sales pipeline mechanics: forecasting, deal inspection, pipeline hygiene, ABM
• Comfortable moving between command line implementation and executive conversation

Tech stack