AI Solutions Strategist, Gtm Applications (remote)

CrowdStrike CrowdStrike · Enterprise · CA · Remote

This role is responsible for leading the design, deployment, and operationalization of agentic AI workflows and enterprise AI solutions across GTM platforms. It involves defining integration patterns for LLM-powered agents, RAG pipelines, and orchestration frameworks, overseeing implementation with human-in-the-loop, and establishing AI deployment standards and guardrails. The role requires strong technical leadership, stakeholder management, and hands-on experience with AI technologies and enterprise integrations.

What you'd actually do

  1. Lead the design, deployment, and operationalization of agentic AI workflows across GTM platforms (Salesforce, Slack, Marketo, CPQ, Snowflake and enterprise systems).
  2. Drive end-to-end delivery of enterprise AI initiatives by partnering with Product Managers, Engineering teams, Security, and Business Stakeholders across the GTM ecosystem.
  3. Define scalable integration patterns for LLM-powered agents, RAG pipelines, orchestration frameworks, and enterprise AI services using LangGraph, CrewAI, MCP, or similar technologies.
  4. Oversee implementation of intelligent workflows with human-in-the-loop escalation, retry handling, observability, and governance controls.
  5. Establish AI deployment standards, reusable design patterns, and operational guardrails for the GTM AI Pod engineering teams.

Skills

Required

  • Enterprise technology, solution delivery, distributed architecture, or product engineering experience
  • Leading enterprise Agentic AI transformation initiatives
  • Hands-on experience designing and deploying AI/LLM-powered enterprise solutions
  • Leading cross-functional programs and managing stakeholder relationships
  • Deep understanding of AI orchestration frameworks (LangGraph, CrewAI, LangChain, Semantic Kernel, or similar)
  • Experience with LLM APIs and enterprise AI platforms (OpenAI, Anthropic, AWS Bedrock, or equivalent)
  • Experience implementing RAG architectures, vector databases, AI observability, and intelligent workflow orchestration
  • Experience with AI governance, prompt security, and AI risk mitigation frameworks
  • Strong understanding of enterprise integrations, APIs, event-driven architectures, and GTM platforms (Salesforce preferred)
  • Guiding engineering teams through implementation while remaining hands-on in solution design and deployment strategy
  • Strong communication, executive presentation, and technical leadership skills

Nice to have

  • MCP (Model Context Protocol) and enterprise AI interoperability patterns
  • GTM and revenue platforms such as Salesforce

What the JD emphasized

  • Lead the design, deployment, and operationalization of agentic AI workflows
  • Drive end-to-end delivery of enterprise AI initiatives
  • Define scalable integration patterns for LLM-powered agents, RAG pipelines, orchestration frameworks
  • Oversee implementation of intelligent workflows
  • Establish AI deployment standards
  • Lead architecture and delivery reviews
  • Define standards for Agentic Development Life cycle
  • Partner with Information Security teams
  • Drive stakeholder alignment
  • Evaluate and recommend AI platforms, vector databases, orchestration tooling
  • Champion adoption of Agentic AI and LLM-powered tooling
  • Stay current with rapidly evolving AI ecosystems, orchestration frameworks, and enterprise AI best practices
  • Experience leading enterprise Agentic AI transformation initiatives
  • hands-on experience designing and deploying AI/LLM-powered enterprise solutions
  • Deep understanding of AI orchestration frameworks
  • Experience implementing RAG architectures, vector databases, AI observability, and intelligent workflow orchestration
  • Experience with AI governance, prompt security, and AI risk mitigation frameworks

Other signals

  • Deploying enterprise AI solutions
  • Agentic AI technologies
  • LLM-powered agents
  • RAG pipelines
  • Orchestration frameworks