CrowdStrike GenAI Security Engineer
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Job description
Solution Design & Development Design and develop scalable enterprise applications using .NET (C#) and Python Build and integrate GenAI-powered features into existing and new systems Develop APIs, microservices, and backend systems for AI-driven applications
Requirements
Role Overview We are looking for a Solutions Expert with strong hands-on experience in .NET and Python, combined with working knowledge of Generative AI (GenAI) technologies. This role is ideal for a senior individual contributor who can design, build, and implement scalable solutions, with a focus on integrating AI capabilities into enterprise applications., Generative AI Implementation Work with: LLM APIs (OpenAI / Azure OpenAI / open-source models) Prompt engineering and optimization Implement: RAG (Retrieval-Augmented Generation) pipelines Embeddings and vector database integrations Build use cases like: Chatbots Document summarization Intelligent search Engineering & Integration Develop microservices-based architectures Integrate AI models into enterprise platforms Work with: REST APIs Cloud platforms (Azure / AWS / Google Cloud Platform) Containers (Docker, Kubernetes good to have) Collaboration Work closely with: Architects Product managers Data/ML engineers Translate functional requirements into technical solutions Quality & Best Practices Write clean, scalable, and maintainable code Follow best practices for: Security Performance optimization Testing and deployment Experience 7 12 years in software development 2+ years working with AI/ML or GenAI use cases Technical Skills Strong expertise in: .NET Core / C# Python (backend / AI integration) Experience with: LLM APIs (OpenAI / Azure OpenAI) LangChain / LlamaIndex (or similar frameworks) Vector databases (Pinecone, FAISS, etc.) Solid understanding of: REST APIs Microservices architecture Preferred Qualifications Experience with cloud-native development (Azure preferred) Exposure to AI-driven application development Familiarity with CI/CD pipelines and DevOps practices What Makes You Successful Strong hands-on coding ability Problem-solving mindset with focus on practical AI implementation Ability to work in a fast-paced, collaborative environment
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