Padmi
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Samba

media intelligence · cross-channel measurement

AI GTM Engineer

San Francisco Bay Area · Onsite$175k–$215k/yrPosted 1 month ago
Machine learningUnspecifiedUs Full Time Salaried
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GTM systems architecture and automation

Design and operate multi-agent systems connecting Salesforce, Gong, Slack, Snowflake, and Samba's proprietary TV data assets into unified, real-time GTM workflows

Build and maintain MCP (Model Context Protocol) servers that give Claude governed, real-time access to our GTM stack, including live Salesforce records, Gong call data, and Samba viewership signals

Eliminate manual data transfer and context-switching for sellers by automating the aggregation, summarization, and routing of deal intelligence across tools

Create RAG pipelines and prompt libraries that give Claude accurate, governed context on our 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

Evals, reliability, and continuous improvement

Design and run structured evals across all production AI systems: measure output quality, accuracy, regression risk, and real business impact, not just vibes

Build eval frameworks that catch prompt drift, model behavior changes, and degraded tool use before they hit sellers in production

Run A/B experiments across workflows to prove what is actually moving pipeline and revenue, not just what looks good in demos

Monitor agentic systems in production and own the feedback loop: what broke, why, and what the fix is

Be the internal authority on Claude across the Revenue Org: best practices, MCP architecture, prompt engineering standards, and enablement

Write documentation and run enablement sessions so sellers and operators extract real value from every system you ship

Signal integration across the sales org

Build systems that automatically 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 a unified account view that sellers can act on without digging through five tools

Design workflow automation that reduces the cognitive load on sellers so they spend more time selling and less time updating CRM fields, hunting for context, or writing the same email for the 40th time

Identify the highest-friction points in our GTM process and systematically eliminate them through automation

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