Sr. Software Engineer - Agentic Workflows (Falcon Cloud Security)

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: The Falcon Cloud Security team is looking for a Senior Engineer to lead the development of Agentic Workflows - a transformative initiative aimed at automating complex security operations using AI-native agents. You will be at the forefront of building autonomous systems that don't just alert but actively reason, investigate, and remediate security risks across multi-cloud environments. As part of this high-impact team, you will design and implement the "brain" of our cloud security platform, leveraging large-scale data and AI-driven logic to help customers discover misconfigurations, prioritize risks, and automate defensive actions at scale. What You’ll Do: Design & Architect: Lead the backend engineering efforts to build autonomous agentic frameworks, moving from rapid prototypes to large-scale production applications. Develop Core Logic: Build and optimize the decision-making engines and workflows that allow security agents to interact with cloud APIs (AWS, Azure, GCP) and internal data streams. Data Integration: Develop high-performance data integrations and streaming services (Kafka) to feed real-time security data into agentic models for continuous reasoning. Scale Systems: Architect distributed systems capable of processing billions of security events to provide actionable posture intelligence and automated remediation. Collaborate: Work in a "startup-like" environment, brainstorming and defining new product features with cross-functional teams in a high-trust, autonomous culture. Mentor: Share your expertise with the team, championing new technologies and raising the technical bar of the engineering organization. The Technology Stack: Languages: Go (Golang), Python, Java. Cloud: AWS, GCP, Azure, and Kubernetes. Data & Streaming: Kafka, Apache Spark, Opensearch, Cassandra, Redis. Infrastructure: Docker, Git. What You’ll Need: Experience: 6+ years of experience in backend development, with strong proficiency in Go and Python. AI/LLM Experience: Prior experience building workflows powered by LLMs, RAG, or autonomous agents. Strong understanding of agent frameworks and understanding of key components including model integration, tool calling patterns, and Model Context Protocol (MCP) Cloud Expertise: Deep knowledge of at least two major cloud providers (AWS, Azure, or GCP). Systems Engineering: Strong understanding of distributed systems, scalability, concurrency, and resilient architecture. Data Proficiency: Solid experience with data modeling, RDBMS (SQL), and distributed caching solutions like Redis. Education: BS/MS in Computer Science or equivalent professional experience in data structures and algorithms. Bonus Points: Cybersecurity Background: Experience in threat detection and response, identity management (IAM), data security or cloud security posture management. Big Data: Experience with analytical databases and petabyte-scale data processing. AI native tools: Familiarity with Loveable, Replit, MCP, n8n. #LI-DM2 Benefits of Working at CrowdStrike: Market leader in compensation and equity awards Comprehensive physical and mental wellness programs ... (truncated, view full listing at source)