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. 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 also a mission-driven company. We cultivate a culture that gives every CrowdStriker both the flexibility and autonomy to own their careers. 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.
About the Role:
This role sits at the intersection of AI application engineering and platform reliability within CrowdStrike’s Core Tech, Go To Market IT Apps Team — a team of Architects, Engineers, QA, BSAs, and Product Owners delivering highly Reliable, Scalable, and Secure Infrastructure and Automation Services across GTM Applications to accelerate Business Velocity and Operational Excellence. As a hybrid AI Engineer (Dev + DevOps), you will build and own the full lifecycle of agentic AI solutions: from designing LLM-powered workflows and autonomous agents to engineering the CI/CD pipelines, infrastructure-as-code, platform observability, and DevSecOps practices that make those solutions production-grade and enterprise-ready. As part of the GTM AI Pod, every member is expected to embrace Agentic AI technologies, operate with an open-source AI engineering mindset, and actively contribute to building the next generation of intelligent GTM workflows. You will not hand off your code to another team to deploy — you own it end to end.
What You’ll Do:
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.
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.
Define scalable enterprise AI architecture patterns: model routing, orchestration, memory management, context-window governance, and multi-tenant isolation strategies.
Design and optimize RAG systems, semantic search pipelines, vector retrieval strategies, and enterprise knowledge-grounding frameworks for GTM data domains.
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.
Build and operate platform observability stacks (tracing, logging, alerting) and AI-specific metrics while managing infrastructure-as-code (Terraform / CDK) across AWS Bedrock and Vertex AI.
Implement DevSecOps and evaluation frameworks: supply-chain security, prompt benchmarking, hallucination reduction, and automated regression testing for non-deterministic outputs.
Define error handling, fallback strategies, and graceful degradation patterns for non-deterministic AI systems, including circuit-breaker patterns at both the application and infrastructure layers.
Retire legacy integrations and replace them with modern, agentic, event-driven architectures, eliminating manual toil through automation and self-healing runbooks.
Champion engineering excellence: code reviews, runbook documentation, blameless post-mortems, and capacity planning that spans both application logic and underlying compute.
Evaluate AI vendors and platforms with a strategic build-vs-buy mindset, factoring in total cost of ownership, compliance posture, and operational burden.
Identify, scope, and automate manual GTM processes to increase organizational leverage and reduce time-to-insight for go-to-market teams.
What You’ll Need:
Bachelor’s degree in Computer Science, Engineering, or a related field.
5+ years of software engineering experience, with meaningful exposure to both application development and platform/infrastructure responsibilities.
Strong proficiency in Python and TypeScript/JavaScript for AI application development, automation scripting, and infrastructure tooling.
Hands-on production experience with agentic AI frameworks, document parsing and structured extraction pipelines, autonomous agents, and LLM-powered systems at enterprise scale.
Solid working knowledge of modern AI orchestration frameworks: LangGraph, Semantic Kernel, CrewAI, AutoGen, MCP, and/or LangChain.
Demonstrable experience building and maintaining CI/CD pipelines (GitHub Actions, Jenkins, or Copado) and practicing GitOps or trunk-based delivery for both application and infrastructure code.
Proficiency with container and orchestration runtimes (Docker, Kubernetes or equivalent) and familiarity with service mesh, secrets management, and configuration management patterns.
Salesforce development experience: Apex, LWC, REST/SOAP integrations, Platform Events, and Agentforce agent actions.
Proficiency with vector databases (Pinecone, pgvector, Weaviate, or similar) and retrieval optimization techniques for RAG systems.
Solid understanding of DevSecOps practices: supply-chain security, SAST/DAST integration, secrets rotation, and least-privilege cloud IAM.
Bonus Points:
Salesforce Platform Developer II, Application Architect, or DevOps Engineer certification.
Experience building Slack apps, Slack Workflow Builder, or Slack-integrated agentic workflows.
Hands-on experience with Salesforce Einstein / Agentforce platform development.
Demonstrated contributions to open-source AI or DevOps tooling (LangChain, LlamaIndex, Terraform providers, or similar).
Exposure to fine-tuning, RLHF, or model evaluation pipelines on domain-specific GTM datasets.
Experience designing or operating model routing platforms, enterprise AI control planes, or multi-model gateway patterns (e.g., LiteLLM, OpenRouter).
Background in platform engineering, SRE, or cloud infrastructure with a measured focus on SLOs, error budgets, and reliability engineering practices.
Familiarity with AI governance, responsible AI frameworks, or MLOps maturity models as they apply to enterprise GTM systems.
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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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