Lead the build of an AI-native revenue organization at Samba TV. Design and operate multi-agent systems integrating Salesforce, Gong, Slack, Snowflake, and proprietary TV data into real-time GTM workflows. Build and maintain MCP servers to provide Claude AI platform governed access to live business data. Automate deal intelligence aggregation and routing to reduce manual work for sellers. Create RAG pipelines and prompt libraries for accurate AI context. Architect AI service integrations using Python and APIs. Design and run structured evaluations of AI systems to measure quality and business impact. Monitor production systems and own feedback loops. Serve as Claude expert and enable users. Build systems to surface deal risk, flag renewals, draft outreach, and score accounts using viewership signals. Connect sales intelligence into unified account views. Automate workflows to reduce seller cognitive load and eliminate friction in GTM processes. Requirements: 3-5 years in software/data engineering or GTM operations with technical depth, ownership of AI/automation functions, production-level Python/JavaScript, hands-on LLM and Claude experience, Salesforce and Gong expertise, Snowflake and dbt knowledge, understanding of sales pipeline mechanics, and ability to communicate across technical and executive audiences.
What you'll do
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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
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
