AI Engineer(remote, Ind)

CrowdStrike CrowdStrike · Enterprise · India · Remote

CrowdStrike is seeking an AI Engineer to build and own the full lifecycle of agentic AI solutions, from designing LLM-powered workflows and autonomous agents to engineering CI/CD pipelines, infrastructure-as-code, platform observability, and DevSecOps practices. The role involves leading engineering delivery for agentic AI capabilities, designing and building LLM-powered workflows and multi-agent systems, defining enterprise AI architecture patterns, optimizing RAG systems, building and maintaining Salesforce integrations, and implementing DevSecOps and evaluation frameworks.

What you'd actually do

  1. Lead engineering delivery for agentic AI capabilities across GTM stakeholders and technology stacks (Salesforce, Slack, third-party apps, and in-house platforms), owning requirements through production deployment and post-release observability.
  2. Design and build LLM-powered workflows, autonomous agents, and multi-agent systems using Agentcore, Slack, Model Context Protocols (MCPs), LangChain, and LangGraph — then ship them via automated pipelines you maintain.
  3. Define scalable enterprise AI architecture patterns: model routing, orchestration, memory management, context-window governance, and multi-tenant isolation strategies.
  4. Design and optimize RAG systems, semantic search pipelines, vector retrieval strategies, and enterprise knowledge-grounding frameworks for GTM data domains.
  5. Build and maintain Salesforce Apex, Lightning Web Components, Platform Events, and Agentforce agent actions, integrating them with AI back-ends through secure, event-driven patterns.

Skills

Required

  • Python
  • TypeScript/JavaScript
  • agentic AI frameworks
  • autonomous agents
  • LLM-powered systems
  • LangGraph
  • LangChain
  • CI/CD pipelines
  • GitOps
  • Docker
  • Kubernetes
  • Salesforce Apex
  • Lightning Web Components
  • Platform Events
  • Agentforce agent actions
  • vector databases
  • RAG systems
  • DevSecOps practices

Nice to have

  • Salesforce Platform Developer II certification
  • Application Architect certification
  • DevOps Engineer certification
  • Slack apps
  • Slack Workflow Builder
  • Slack-integrated agentic workflows
  • Salesforce Einstein
  • Agentforce platform development
  • LangChain contributions
  • LlamaIndex contributions
  • Terraform contributions

What the JD emphasized

  • own the full lifecycle of agentic AI solutions
  • own it end to end
  • production deployment and post-release observability
  • production-grade and enterprise-ready
  • enterprise scale
  • production experience

Other signals

  • building and owning the full lifecycle of agentic AI solutions
  • designing LLM-powered workflows and autonomous agents
  • engineering the CI/CD pipelines, infrastructure-as-code, platform observability, and DevSecOps practices