AI Platform Engineer (remote)

CrowdStrike CrowdStrike · Enterprise · United States · Remote

AI Platform Engineer responsible for scaling AI infrastructure, enabling agentic security and identity, building and managing environments for AI vendors and components, technology evaluation, cross-functional R&D, agent observability, and driving innovation for internal AI agents. The role bridges rapid prototyping and scalable infrastructure, focusing on API-driven AI technologies and high-code agent environments.

What you'd actually do

  1. Scale AI Infrastructure: Implement and scale critical infrastructure for advanced agents in cloud environments (AWS, GCP), working closely with developers to transition rapid prototypes into robust, scalable solutions
  2. Enable Agentic Security & Identity: Implement advanced AI Gateways and integrate Okta for robust agent identity and security posture
  3. Build & Manage Environments: Create and maintain agile environments dedicated to testing and prototyping new AI vendors, components, models, and integrations, while carving a clear path to production releases
  4. Technology Evaluation: Develop and execute rigorous evaluation criteria for emerging AI technologies, ensuring we adopt the best tools for our high-code agent environments
  5. Cross-Functional R&D: Function as a key technical pivot point in a group focused on rapid prototyping, collaborating seamlessly with Information Security, Identity, and wider IT teams. Partner with enterprise architects to align rapid prototypes with broader architectural standards, helping to validate and offer critical feedback

Skills

Required

  • Python/Typescript
  • containerization (Docker/Kubernetes)
  • REST APIs
  • identity protocols (OAuth2, OIDC)
  • cloud environments (AWS/GCP)
  • Terraform
  • CI/CD pipelines for agentic innovations
  • model deployments
  • high-code AI workflows
  • R&D or rapid prototyping environments
  • methodically evaluate new vendor technologies
  • set testing criteria
  • present actionable findings
  • collaborative communication
  • AI-specific threat vectors (e.g., OWASP Top 10 for LLMs)
  • implementing runtime AI guardrails
  • securing non-human/machine identities at scale

Nice to have

  • Okta integration

What the JD emphasized

  • critical infrastructure
  • robust, scalable solutions
  • advanced AI Gateways
  • rigorous evaluation criteria
  • rapid prototyping
  • architectural standards
  • reliability at scale
  • rapid cloud prototypes
  • scalable Terraform architectures
  • experimental concepts
  • actionable findings
  • AI-specific threat vectors
  • runtime AI guardrails
  • non-human/machine identities

Other signals

  • scaling infrastructure for internal agents
  • implementing custom API-driven AI technologies
  • enabling high-code agent environments
  • agentic security
  • evaluating new vendors and technologies
  • building infrastructure for next-generation AI agents