Sr. Full Stack Engineer (remote)

CrowdStrike CrowdStrike · Enterprise · United States · Remote

This role focuses on building an agentic AI platform for marketing automation. The engineer will architect and develop the infrastructure, including AI agents, orchestration pipelines, data foundations, and UIs, to automate end-to-end marketing workflows. The role requires full-stack engineering experience with Python and modern JavaScript/TypeScript, production experience with LLM/AI APIs, and demonstrated experience building agentic workflows and evaluation frameworks.

What you'd actually do

  1. Build integrations: connecting the AI campaign engine to CrowdStrike's marketing stack — work management platforms (e.g., Workfront), marketing automation systems (e.g., Marketo), collaboration tools (Google Docs, Slack), CMS, and digital asset management systems
  2. Develop the orchestration layer: that manages multi-agent pipelines, state persistence, error recovery, and parallel execution
  3. Design and build intuitive web UIs: that make AI-powered workflows accessible to non-technical marketing users — campaign dashboards, workflow builders, approval interfaces, and real-time pipeline status views
  4. Create production tooling: including HTML/email template generation from agent outputs, design asset pipelines (PPTX, PDF, SVG), and content publishing workflows
  5. Build analytics infrastructure: performance dashboards, agent quality scoring, A/B test tracking, and feedback loops from distribution metrics back into the agent system

Skills

Required

  • 8+ years of full-stack engineering experience with Python and modern JavaScript or TypeScript
  • Frontend engineering experience: you've built production web applications with React (or equivalent) and understand how to design interfaces that drive adoption with non-technical users
  • Production experience with LLM/AI APIs: you've built and shipped systems that call Claude, GPT, or similar models at scale, and you understand token management, rate limiting, error handling, reliability, and cost optimization
  • Demonstrated experience with AI agents: you've designed, built, and deployed agentic workflows that transformed real work, not just isolated experiments
  • Experience building evaluation frameworks: for AI systems, including prompt evals, output quality scoring, benchmarking, and testing against clear baselines
  • Strong systems design skills: you can architect a multi-service platform, design APIs, and make infrastructure decisions that hold up as the system scales
  • Integration experience: you've connected systems via REST APIs, webhooks, OAuth, and worked with enterprise tools (project management, CMS, marketing automation platforms)
  • A strong builder mindset: you would rather ship a working v1, learn quickly, and iterate than spend a quarter talking about what might be possible. You thrive in ambiguity, make smart architectural calls, and create clarity where none exists yet
  • Strong communication skills and a genuine ability to translate technical concepts for non-technical audiences
  • Working knowledge of CI/CD, containerization, cloud infrastructure, and observability (AWS preferred)

What the JD emphasized

  • agentic AI platform
  • automates end-to-end workflows
  • AI agents and orchestration pipelines
  • production-grade integrations
  • enterprise-grade system
  • AI APIs
  • agentic workflows
  • evaluation frameworks

Other signals

  • AI agents
  • orchestration pipelines
  • production-grade integrations
  • enterprise-grade system
  • AI APIs
  • evaluation frameworks