Lead AI Engineer- Gtm Systems

Samsara Samsara · Enterprise · Atlanta, GA · Business Systems

Lead AI Architect for Go-To-Market (GTM) Systems, defining the technical vision for AI-powered automation. This role involves architecting, prototyping, and establishing patterns for low-code platforms and custom agentic pipelines, integrating them into an enterprise-grade system. Responsibilities include leading architectural design for complex GTM systems, driving the adoption of AI tools, and serving as a technical authority on LLM orchestration.

What you'd actually do

  1. Define and own the technical vision for AI-powered GTM systems — establishing the architecture strategy that covers both low-code automation (Workato, MuleSoft, Salesforce Flow) and custom agentic AI builds (LangGraph, LangChain, MCP-enabled pipelines)
  2. Create and publish the reference architectures, design patterns, and decision frameworks that guide when and how the GTM engineering team builds: low-code-first vs. custom, synchronous vs. event-driven, human-in-the-loop vs. fully automated
  3. Lead architectural design for the highest-complexity GTM systems — multi-system integrations, enterprise-scale agentic workflows, real-time event processing, and cross-platform data orchestration across Salesforce, NetSuite, Marketo, and custom data stores
  4. Drive the evaluation, selection, and adoption of emerging AI tools, frameworks, and platforms — assessing fit, risk, and maturity to ensure Samsara stays at the leading edge without accumulating technical debt
  5. Serve as the organization's technical authority on LLM orchestration: prompt safety, retrieval-augmented generation, model context management, tool calling, multi-agent coordination, and responsible AI design

Skills

Required

  • Technical vision for AI-powered GTM systems
  • Architecture strategy for low-code automation and custom agentic AI builds
  • Reference architectures, design patterns, and decision frameworks
  • Architectural design for complex GTM systems (integrations, agentic workflows, event processing, data orchestration)
  • Evaluation, selection, and adoption of AI tools, frameworks, and platforms
  • LLM orchestration (prompt safety, RAG, model context management, tool calling, multi-agent coordination, responsible AI)
  • Integration architecture strategy
  • Low-code-first strategy governance
  • Translating strategic business goals into architectural roadmaps

Nice to have

  • Experience with Workato, MuleSoft, Salesforce Flow
  • Experience with LangGraph, LangChain
  • Experience with Salesforce, NetSuite, Marketo

What the JD emphasized

  • architect
  • architectural blueprints
  • architectural roadmaps
  • architectural design
  • architectural vision
  • architecture strategy
  • reference architectures
  • enterprise-grade system
  • enterprise integration
  • enterprise-scale agentic workflows
  • enterprise AI

Other signals

  • AI-powered automation
  • agentic pipelines
  • low-code platforms
  • custom agentic AI builds
  • enterprise-grade system
  • LLM orchestration