Sr. Platform Engineer, AI Infrastructure (Remote)

As a global leader in cybersecurity, CrowdStrike protects the people, processes and technologies that drive modern organizations. Since 2011, our mission hasn’t changed — we’re here to stop breaches, and we’ve redefined modern security with the world’s most advanced AI-native platform. We work on large scale distributed systems, processing almost 3 trillion events per day and this traffic is growing daily. Our customers span all industries, and they count on CrowdStrike to keep their businesses running, their communities safe and their lives moving forward. We're proud to work for a mission-driven company leveraging AI to transform the way we work. CrowdStrikers drive their careers through flexibility and autonomy while also being expected to contribute to a culture of responsible AI adoption, experimentation, and innovation. We use an AI-first mindset as a force multiplier to proactively and continuously accelerate execution, build expertise, uncover insights, and solve complex problems. We’re always looking to add talented CrowdStrikers to the team who have limitless passion, a relentless focus on innovation and a fanatical commitment to our customers, our community and each other. Ready to join a mission that matters? The future of cybersecurity starts with you.

The Enterprise AI space is evolving at an unprecedented pace, and so is our project portfolio. We are seeking a highly versatile, hands-on AI Infrastructure Engineer to join the AI Platforms team within IT Enterprise AI.

In this role, you will build and operate the cloud, platform, deployment, identity, networking, security, and observability infrastructure that powers CrowdStrike’s internal AI agents and services. You will serve as the critical bridge between rapid AI prototyping and secure, scalable, production-ready platforms.

This is primarily a platform and infrastructure engineering role rather than an AI application development role. You will partner closely with AI developers to take prototypes and experimental services into production by establishing the infrastructure, automation, security controls, deployment patterns, and operational capabilities they need to run reliably at scale.

The ideal candidate comes from a Platform Engineering, DevOps, Site Reliability Engineering, Cloud Infrastructure, or Developer Infrastructure background and has experience supporting modern applications — ideally AI, ML, or API-driven workloads — in production.

You will work closely with AI developers, InfoSec, Identity, Cloud, and other cross-functional teams to enable secure high-code AI environments, agent infrastructure, and emerging enterprise AI platforms.

If you enjoy solving complex infrastructure problems, evaluating rapidly evolving technologies, and building the foundational systems that allow engineering teams to move quickly and securely, this role is for you.
 

• Build and Scale AI Infrastructure: Design, deploy, and operate production infrastructure supporting internal AI agents, services, and platforms across AWS and/or GCP, including compute, networking, storage, private connectivity, security controls, and runtime environments.

• Own Infrastructure as Code: Build and maintain repeatable, secure cloud infrastructure using Terraform or equivalent Infrastructure-as-Code tooling, enabling consistent deployment across development, testing, and production environments.

• Manage Containerized Workloads: Deploy and operate services using Docker, Kubernetes, and container-based runtime platforms, establishing scalable deployment patterns for AI services and agent workloads.

• Build CI/CD and GitOps Workflows: Design and maintain automated build, test, deployment, and environment-management pipelines using technologies such as GitHub Actions, GitLab CI, Jenkins, ArgoCD, Flux, or similar tooling.

• Implement Identity and Access Patterns: Partner with Identity and Security teams to implement secure authentication, authorization, secrets management, and machine-to-machine access using technologies and standards such as Okta, OAuth2, OIDC, Vault, IAM, and cloud-native secrets management.

• Build Secure AI Gateway Infrastructure: Implement and operate API and AI gateway patterns that securely connect internal applications and agents to models, enterprise services, and external APIs.

• Own Platform Observability: Build monitoring, logging, metrics, distributed tracing, and alerting capabilities using technologies such as OpenTelemetry, Prometheus, Grafana, Datadog, or equivalent platforms.

• Productionize AI Services: Partner with AI engineers and developers to transform prototypes into secure, reliable, observable, scalable, and operationally supportable production services.

• Engineer Cloud Networking: Design and troubleshoot networking patterns including VPCs, private endpoints, routing, security groups, service connectivity, and secure access between cloud and enterprise environments.

• Enable Agent and MCP Infrastructure: Build and support the infrastructure required to securely deploy and operate AI agents, MCP servers, model integrations, and supporting services.

• Improve Platform Reliability: Establish standards for availability, performance, scalability, deployment safety, rollback, environment management, and operational readiness.

• Evaluate Emerging Technologies: Rapidly assess new AI infrastructure, cloud, security, gateway, and developer-platform technologies and determine how they can be safely incorporated into CrowdStrike’s enterprise environment.

• Collaborate Across Teams: Work closely with AI Engineering, InfoSec, Identity, IT, Cloud, and other stakeholders to ensure new AI capabilities meet enterprise standards for security, reliability, scalability, and operational readiness.

• 5+ years of hands-on experience in Platform Engineering, Cloud Infrastructure, DevOps, Site Reliability Engineering, Developer Infrastructure, or a closely related field, with meaningful ownership of production environments.

• Strong hands-on experience designing, deploying, and operating infrastructure in AWS and/or GCP.

• Production experience with Docker, Kubernetes, and containerized application deployment.

• Hands-on experience provisioning and managing infrastructure using Terraform or another Infrastructure-as-Code framework.

• Experience designing, building, or maintaining CI/CD and/or GitOps pipelines.

• Strong understanding of cloud networking, including VPCs, private connectivity, routing, security groups, load balancing, and service-to-service communication.

• Experience implementing identity, authentication, authorization, and secrets-management patterns using technologies such as IAM, Okta, OAuth2/OIDC, Vault, or cloud-native equivalents.

• Experience implementing observability for distributed applications, including logging, metrics, tracing, monitoring, and alerting.

• Strong scripting or software engineering skills in Python, Go, TypeScript, or similar languages, particularly for infrastructure automation, APIs, platform tooling, and integrations.

• Experience troubleshooting complex production systems across infrastructure, networking, application, authentication, and deployment layers.

• Strong understanding of modern software delivery and production operations, including automation, scalability, reliability, security, environment management, and operational support.

• Ability to work effectively in a fast-moving R&D environment where requirements and technologies evolve quickly.

• Strong communication skills and the ability to work across AI Engineering, Infrastructure, Security, Identity, and other technical teams.
   

• Experience building or operating infrastructure supporting LLMs, GenAI applications, AI agents, or ML workloads.

• Experience implementing or operating AI gateways, API gateways, model gateways, or model-routing infrastructure.

• Familiarity with agent frameworks such as LangGraph, LangChain, Google ADK, or similar technologies.

• Experience deploying or operating MCP servers and related agent integration infrastructure.

• Familiarity with RAG architectures, vector databases, LLM evaluation, or agent orchestration.

• Experience supporting enterprise AI platforms or integrating services such as Amazon Bedrock, Google Vertex AI, Azure OpenAI, or similar model platforms.

• Knowledge of AI-specific security considerations, including agent identity, access controls, data protection, model access, and runtime guardrails.

• Experience building internal developer platforms, self-service infrastructure, reusable deployment patterns, or paved-road engineering experiences.

You will help CrowdStrike move AI capabilities from experimentation into production by creating infrastructure that is secure, automated, observable, scalable, and easy for AI developers to consume.

You do not need to be the person building every agent or AI application. You should be the engineer who understands how to deploy it, secure it, connect it, monitor it, scale it, and keep it running in production.

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Benefits of Working at CrowdStrike:

• Market leader in compensation and equity awards

• Comprehensive physical and mental wellness programs 

• Competitive vacation and holidays for recharge  

• Paid parental and adoption leaves

• Professional development opportunities for all employees regardless of level or role

• Employee Networks, geographic neighborhood groups, and volunteer opportunities to build connections

• Vibrant office culture with world class amenities

• Great Place to Work Certified™ across the globe

CrowdStrike is proud to be an equal opportunity employer. We are committed to fostering a culture of belonging where everyone is valued for who they are and empowered to succeed. We support veterans and individuals with disabilities through our affirmative action program.

CrowdStrike is committed to providing equal employment opportunity for all employees and applicants for employment. The Company does not discriminate in employment opportunities or practices on the basis of race, color, creed, ethnicity, religion, sex (including pregnancy or pregnancy-related medical conditions), sexual orientation, gender identity, marital or family status, veteran status, age, national origin, ancestry, physical disability (including HIV and AIDS), mental disability, medical condition, genetic information, membership or activity in a local human rights commission, status with regard to public assistance, or any other characteristic protected by law. We base all employment decisions--including recruitment, selection, training, compensation, benefits, discipline, promotions, transfers, lay-offs, return from lay-off, terminations and social/recreational programs--on valid job requirements.

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