CrowdStrike

Infrastructure Engineer

• Design and implement scalable hybrid multi-cloud Kubernetes platform solutions using your deep expertise in cloud-native infrastructure architecture and operations at scale
• Optimize and maintain high reliability of large-scale infrastructure platform systems
• Evaluate and integrate open-source technologies into existing systems workflows
• Provide insights and technical direction for the continued evolution of Kubernetes infrastructure services
• Mentor and help develop less-senior engineers to drive collaborative technical decision-making for infrastructure choices

Senior Infrastructure Engineer – Kubernetes

Backend Engineer

• Lead the design and implementation of core platform services that ingest, process, and route security events from different sources to various execution contexts.
• Drive the architecture for the Detection Content Management Platform (DCMP/CMS), creating advanced CI/CD and DevOps tooling to enable content authors to treat detections as code.
• Develop highly scalable and fault-tolerant microservices, leveraging languages like Go and technologies such as Kubernetes, Flink, and distributed databases (e.g., RocksDB).
• Contribute to the evolution of the Unified Detections Management (UDM) system, ensuring a consistent and comprehensive detection experience for all customers.
• Serve as a technical leader, mentoring mid-level and senior engineers, and driving cross-functional alignment on complex technical challenges.
• Architect and implement features related to cross-cutting concerns like Policy, Flight Control, and Observability, ensuring platform stability and operational excellence.
• Collaborate closely with Product Management and other engineering teams (Engine, UDM, Content) to translate strategic vision into well-defined, executable technical roadmaps.

Senior Backend Engineer

Backend Engineer III

AI Engineer

• Lead engineering delivery for agentic AI capabilities for GTM stakeholders across its technology stack (Salesforce, Slack, 3rd party apps) and In-House Platforms
• Design and build LLM-powered workflows, autonomous agents, multi-agent systems and AI-enhanced integrations using Agentcore, Slack, MCPs, Langchain
• Define scalable enterprise AI architecture patterns including model routing, orchestration, memory management and governance strategies
• Design and optimize Retrieval Augmented Generation (RAG) systems, semantic search pipelines, vector retrieval strategies and enterprise knowledge grounding frameworks
• Build and maintain Apex, Lightning Web Components, Salesforce Platform Events, and Agentforce agent actions
• Implement AI evaluation frameworks including prompt quality benchmarking, hallucination reduction and model performance monitoring
• Mentor senior and mid-level engineers; conduct code reviews and enforce AI engineering standards
• Define error handling, fallback strategies, and graceful degradation patterns for non-deterministic AI systems
• Retire legacy integrations and replace them with modern, agentic, event-driven patterns
• Champion security-first AI engineering: input validation, output sanitization, and prompt injection hardening
• Architect and implement CI/CD pipelines, deployment automation, and platform observability
• Embrace Agentic AI and LLM-powered tooling as a core part of your engineering practice
• Stay current with rapidly evolving AI/ML technologies and apply them pragmatically to GTM systems
• Champion automation-first thinking — if it can be agentic, make it agentic
• Build internal tools and apps to streamline data access and GTM decision-making
• Implement data governance and monitoring frameworks to enhance GTM system quality
• Evaluate vendors and AI platforms with a strategic build vs. buy mindset
• Identify and automate manual processes to increase organizational leverage

Lead AI Engineer, GTM Applications

Software Engineer

• Manage regional training coordinators and team trainers, ensuring alignment to Training & Onboarding processes, SOPs, and expectations.
• Oversee onboarding and training for all new hires in your region, ensuring a consistent, high-quality experience and timely progression through required learning paths.
• Support the ongoing maintenance and evolution of training content by updating materials as processes change, tracking content health, and ensuring onboarding reflects current tools, workflows, and best practices.
• Provide real-time training and system support within the region, contributing to a follow-the-sun model for key platforms that Training and Onboarding use.
• Partner with Curriculum Developers to support the creation, maintenance, and continuous improvement of training content, including contributing regional insights, assisting with content development, and ensuring materials remain accurate, relevant, and aligned to operational needs.
• Monitor training data and metrics to identify knowledge gaps, regional trends, or performance challenges — and propose solutions or targeted interventions.
• Support intake and prioritization of regional training needs, ensuring alignment with the broader training strategy and organizational roadmap.
• Maintain close communication with regional leaders, onboarding leads, and cross-functional partners to ensure visibility into progress, challenges, and upcoming initiatives.
• Ensure consistent adoption of T&O-owned onboarding standards and content within your region, while tailoring the delivery and operational execution to accommodate regional workflows and schedules.
• Maintain documentation, JIRA tickets, and training records to support operational transparency and continuous improvement.
• Deliver hands-on training or support facilitation on an as-needed basis.

Associate Curriculum Developer, Regional Training Lead

Product Marketing

• Own the AI product roadmap for GTM apps team, aligned with business OKRs and AI strategy.
• Identify AI opportunities in Lead-to-Cash and customer Success processes by driving Business workshops, ideation sessions and Executive meetings.
• Define, prioritize, and groom the backlog for agentic workflows (autonomous agents, AI Assisted Workflows and LLM Integrations) across Sales, Marketing, and Customer Success platforms.
• Translate business requirements into clear epics, user stories, and acceptance criteria for engineering.
• Make effective Build Vs Buy decisions on Agentic capabilities in complex applications environment
• Partner with Business to Define and track AI-specific KPIs: model accuracy, agent task completion rate, hallucination rate, business ROI, data privacy compliance, fairness reviews, and responsible use policies.
• Design and champion prompt engineering standards and context-window optimization strategies across GTM features.
• Partner with Data and Analytics teams to ensure GTM data is AI-ready: clean, structured, and access-governed.
• Evangelize AI-first product thinking and drive AI adoption metrics across the GTM IT organization.
• Embrace Agentic AI and LLM-powered tooling as a core part of your practice.
• Stay current with rapidly evolving AI/ML technologies and apply them pragmatically to GTM systems.
• Champion automation-first thinking — if it can be agentic, make it agentic.

Senior Manager, AI Product Owner, GTM Applications

Engineer

• Lead backend engineering efforts from rapid prototypes to large-scale applications across CrowdStrike products
• Leverage and build cloud based systems to detect targeted attacks and automate cyber threat intelligence production at a global scale
• Brainstorm, define, and build collaboratively with members across multiple teams
• Obsess about learning, and champion the newest technologies & tricks with others, raising the technical IQ of the team
• Be mentored and mentor other developers on web, backend and data storage technologies and our system
• Constantly re-evaluate our product to improve architecture, knowledge models, user experience, performance and stability
• Be an energetic ‘self-starter’ with the ability to take ownership and be accountable for deliverables
• Use and give back to the open source community

Senior Engineer, Cloud – Provisioning Platform

Operations

• Design and implement automated cost monitoring, alerting, and optimization solutions across cloud platforms
• Develop and maintain cost allocation algorithms and tagging strategies for accurate cost attribution
• Build integrations between cloud billing APIs and internal cost management systems
• Create technical documentation and best practices for cost-efficient infrastructure patterns
• Collaborate with platform teams to implement cost optimization recommendations
• Develop tooling and automation to support FinOps processes across fourteen product groups and eleven platform groups
• Build dashboards and reporting mechanisms for real-time cost visibility
• Implement cost guardrails and automated policies to prevent cost overruns
• Design scalable solutions for cost data collection, processing, and analysis
• Contribute to the TechOps Analytics Data Solution FinOps requirements
• Partner with product engineering teams to identify and implement cost optimization opportunities
• Work closely with Infrastructure Foundations Program to align technical solutions with FY27 Cost Reduction Program
• Support FinOps Working Group with technical expertise and implementation guidance
• Collaborate with Data Analytics Team on cost data pipeline development
• Provide technical input for FinOps capability development roadmap
• Research and evaluate new cost optimization tools and techniques
• Contribute to FinOps governance structures and technical standards
• Mentor junior engineers on cost-conscious engineering practices
• Stay current with cloud platform pricing changes and optimization opportunities

Engineer III – Data Center FinOps

Full-stack Engineer

• Collaborate with all the sensor development teams, across the company, on architecture and strategic initiatives
• Conceptualize and develop new product features
• Provide guidance and support to development teams in designing and implementing software for cross-platform delivery (Windows, macOS, Linux)
• Take ownership of features throughout the entire lifecycle, from initial design to final delivery, including presenting product demonstrations at the conclusion of each sprint
• Engage in cross-functional collaboration with teams situated in various locations

Senior Software Engineer II, MacOS Sensor

Recruitment

• Demonstrated track record of managing and leading a product and engineering recruitment team.
• Inspire, grow and nurture a team of recruiting professionals to deliver against Business hiring needs while meeting quality expectations
• Providing mentorship, guidance and career development to members of your team
• Collaborate with key business leadership partners to understand future plans and develop a global strategy to deliver on these plans
• Define overall recruiting performance goals across the team
• Lead and develop recruiting managers to scale their teams
• Champion recruiting process improvements on a global level for scalability.
• Exceptional ability to direct source, hard to find niche candidates utilizing creativity thru LinkedIn Recruiter, internal and external networks and other sites to perform Boolean searches.
• Ability to compose compelling email campaigns that highlight the exciting technical challenges and incredible culture at CrowdStrike.
• Showcase your talent by attracting and engaging with candidates through your external efforts and creativity.
• Maintain accurate and thorough documentation within the company's ATS.
• Focus on providing a great candidate experience at every opportunity through exceptional written and verbal communication.
• Ability in identifying and assessing a strong candidate pool.
• Strong attention to detail while operating with a sense of urgency.
• Liaise closely with recruiters and hiring managers to understand technical requirements of position and function.
• Demonstrated ability to leverage AI-powered tools and emerging technologies to improve recruiting effectiveness, candidate engagement, and operational efficiency.

Manager, Talent Acquisition – Product and Engineering

• Work on building a platform that powers developing and running data connectors at scale with quality.
• Build generic data connectors such as file ingestion framework, websocket, Rest APIs that can process large amounts of data with low latency
• Developer platform features like integrations certification, easy development, testing and deployment
• Solve hard problems in distributed systems, including high availability, reliability, performance and cost optimizations
• Develop platform / systems in Go & Python. Support globally available, multi-region systems in production
• Lead and participate in cross-team platform-level initiatives and projects
• Work in a team of friendly, trustworthy and knowledgeable colleagues
• Do best practices in software development; code review, automated tests, agile development, retrospective, incremental improvements and continuous deployment
• Troubleshoot critical production issues
• Participate in scoping, designing and developing of new features
• Continuous improvement of internal tools and processes
• Contribute to internal SDKs and connector runtime infrastructure to enable other developers to build and deploy integrations for new 3rd party data sources.

Senior Backend Engineer – Cloud

Data Scientist

• Work at the intersection of Artificial Intelligence and Threat Research
• Work closely with subject-matter experts in cybersecurity to understand analyst workflows and their security operations procedures
• Post-train LLMs and agents — supervised fine-tuning and reinforcement learning (RLHF/RLAIF, PPO/GRPO/DPO, reward modeling) — to automate analyst procedures and improve reliability on real security tasks
• Devise AI agents and combine them into increasingly complex workflows: planning and reasoning loops, tool and function calling, and retrieval and memory
• Research new approaches to agentic planning, and prototype state-of-the-art methods from the literature
• Establish objective criteria for benchmarking agentic systems — evals, LLM-as-judge pipelines, and trajectory-level metrics, with real statistical rigor
• Optimize prompts and inference to get the most out of every model
• Collaborate and coordinate across Engineering, Data Science, and Managed Services teams, and partner with engineers to take prototypes toward production
• Keep track of developments in the field of Artificial Intelligence and help identify, define, and prioritize areas for research

• 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
• Develop the orchestration layer: that manages multi-agent pipelines, state persistence, error recovery, and parallel execution
• 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
• Create production tooling: including HTML/email template generation from agent outputs, design asset pipelines (PPTX, PDF, SVG), and content publishing workflows
• Build analytics infrastructure: performance dashboards, agent quality scoring, A/B test tracking, and feedback loops from distribution metrics back into the agent system
• Design, build, and deploy custom AI agents: and agentic workflows that integrate AI APIs, MCP servers, automation platforms, and enterprise systems into our GTM motion
• Implement auth, permissions, and multi-tenancy: so multiple marketing teams and campaign owners can run pipelines concurrently with appropriate access controls
• Own CI/CD and reliability: automated testing for agent outputs, regression detection, deployment pipelines, monitoring and alerting
• Optimize performance: caching, parallelization, and cost management for LLM API calls across high-volume campaign runs
• Partner closely with Performance Marketing, Digital Intelligence, Engineering, and marketing leadership: to ensure the roadmap is technically sound, operationally meaningful, and connected to business outcomes

Senior Full Stack Engineer

Sales

• Identify, develop and execute account strategy to close new business opportunities and expanding revenue with customers across the assigned region; independently and cooperatively
• Scope, negotiate and bring to closure agreements to exceed booking and revenue quota targets
• Target and gain access to decision makers in key prospect accounts in the assigned territory
• Establish access and maintain existing relationships with key decision makers (typically at the CIO and CSO level) in industry, partners, and enterprise customers to drive all pertinent issues related to sales strategy and goal attainment
• Collaborate with operative peers across functions (including the Field Sales, Channel, Marketing, Sales Operations, System Engineering, Services, Customer Support, and Product Development) to create visibility with target accounts and drive engagement of target prospects at both the individual contributor and executive level
• Work cooperatively with partners to leverage their established account presence and relationships
• Capture, maintain, and disseminate accurate and relevant prospect information using Salesforce.com

Regional Sales Manager – Majors

Data Engineer

• Architect, implement, and optimize data platforms and pipelines specifically designed to support LLMs, Retrieval-Augmented Generation (RAG), and sophisticated AI agentic systems at Exabyte scale.
• Drive the adoption and deployment of agentic workflows and agent harnessing techniques to create autonomous, data-driven security features.
• Design and implement highly scalable, fault-tolerant, and cost-effective data solutions, emphasizing rapid iteration and high-quality deployment.
• Write elegant, production-ready code with a focus on performance, maintainability, and testing rigor, ensuring the ability to ship fast without compromising quality.
• Provide technical leadership and deep expertise in data modeling, normalization, and semantic cataloging for AI/ML workloads.
• Establish best practices for MLOps/DataOps surrounding LLMs, including monitoring, observability, and zero-touch recovery mechanisms for AI services.
• Actively mentor engineers, conducting technical workshops, leading design reviews, and strengthening the team's knowledge in cutting-edge AI platform technologies.
• Collaborate across the organization with Data Scientists, Product Managers, and other engineering teams to transform research prototypes into robust, production-grade services.
• Own the end-to-end lifecycle of critical data services: development, testing, deployment, and monitoring.