Sr. Software Engineer (Remote, ROU)

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. We have 3.44 PB of RAM deployed across our fleet of C* servers - 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 also a mission-driven company. We cultivate an inclusive 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:
Join CrowdStrike's GenAI Hub team to help build and scale our internal Generative AI platform. You'll develop robust backend services that power AI-driven solutions across CrowdStrike, from RAG-based knowledge retrieval to complex agentic workflows. Our platform serves thousands of CrowdStrikers daily, enabling both individual productivity and integration of GenAI capabilities into customer-facing products.

About the Team:
You'll join a high-performing team of experienced engineers building CrowdStrike's central GenAI platform. We operate in a fast-paced, startup-like environment where autonomy, ownership, and quick delivery are valued. Our team embraces the "One Team, One Fight" motto, collaborating closely with other engineering teams, data scientists, PMs, UX designers, and stakeholders across the globe.

What You'll Do:

• Design and implement scalable backend services using Go in a cloud-native environment

• Build reusable platform components and frameworks that other teams can leverage for their GenAI use-cases

• Develop and operate secure LLM deployments in both cloud and on-prem environments

• Create deep integrations with internal systems and establish frameworks for future connectors

• Build high-performance data processing pipelines for document handling and RAG implementations

• Engage directly with internal users across departments to understand requirements and provide technical consultation

• Own features end-to-end, from design through deployment and operation

• Drive innovation by staying current with the rapidly evolving AI landscape

What You'll Need:

• 6+ years of software engineering experience

• Strong proficiency in Go or similar backend languages

• Deep understanding of cloud-native architectures and microservices

• Experience with AWS services and cloud infrastructure

• Practical knowledge of operating production services - CI/CD, monitoring (Grafana, Prometheus), and Kubernetes

• Strong grasp of multithreading, concurrency, and parallel processing

• Experience building and maintaining REST APIs

• Understanding of engineering best practices - code reviews, testing, resilient architecture

• Excellent problem-solving and debugging skills

• Strong written and verbal communication skills

Bonus Points:

• Self-starter mentality with proven ability to drive projects independently

• Comfortable managing multiple competing priorities in a fast-paced environment

• Proactive in identifying and solving technical challenges

• Strong collaboration skills for working with diverse stakeholders

• Ability to make technical decisions with incomplete information

• Interest in AI/ML technologies and staying current with GenAI developments

• Experience with LLM integrations or AI/ML platforms

• Knowledge of vector databases and RAG implementations

• Understanding of message queues and event-driven architectures

• Background in enterprise SaaS products

• Experience with cybersecurity products

• Track