CrowdStrike AI Security Engineer

Role

Seeking a Technical AI Solution Engineer to design, architect, develop, and deliver AI and Generative AI (GenAI) solutions across customer needs. This is a hybrid contract role (Dallas, TX or Atlanta, GA) for 3–6 months with an expected commitment of ~3–6 hours per day. The engineer will lead end-to-end solutions from ideation and PoC/MVP development to production deployment.

Key Responsibilities

• Lead end-to-end design of AI/GenAI solutions: system architecture, data flows, model selection, and integration patterns.
• Partner with customers, product managers, and business teams to identify high-impact AI use cases and gather requirements.
• Evaluate AI technologies, frameworks, and vendors to recommend solution approaches.
• Build hands-on PoCs, MVPs, and production-grade features using Vibe coding, LLMs, embeddings, retrieval, agents, and advanced AI pipelines.
• Implement AI workflows such as MCP, RAG, fine-tuning, prompt engineering, agentic orchestration, and model optimization.
• Develop integrations with enterprise systems, APIs, data platforms, and cloud environments (Azure, AWS, Google Cloud Platform).
• Serve as a subject-matter expert on modern AI, GenAI, and LLM-based architectures and stay current with AI infrastructure, vector databases, and agentic automation.
• Optionally conduct demos, workshops, and knowledge-sharing sessions with clients and teams.

Requirements

• Strong hands-on experience with LLMs, GenAI frameworks, and modern AI stacks (examples cited: OpenAI, Azure OpenAI, Anthropic, Meta Llama).
• Experience building AI pipelines and architectures (MCP, RAG), agents/multi-agent orchestration, prompt engineering and evaluation, and fine-tuning/parameter-efficient training (LoRA, adapters).
• Proficiency with Vibe coding and AI code-generation tools.
• Proficiency in Python and/or Node.js and experience with libraries/frameworks such as LangChain, Semantic Kernel, LlamaIndex; ML frameworks like PyTorch or TensorFlow are optional.
• Experience with vector databases (Pinecone, Weaviate, Chroma, Redis Vector) and cloud AI services (Azure, AWS, Google Cloud Platform).
• Strong understanding of API architectures, microservices, DevOps, CI/CD, and containerization.
• Solution engineering skills: translate business needs into scalable AI designs, interact with customers, gather requirements, present technical solutions, and produce documentation and architecture diagrams.

Preferred / Nice to Have

• Experience in telco, media, or large enterprise environments.
• Knowledge of data engineering, ETL pipelines, feature stores.
• Experience with MLOps/LLMOps methodologies and tooling, vector search optimization, knowledge graphs, or reinforcement learning.
• Familiarity with responsible AI, security, governance, and compliance.

Experience & Education

• ~5–10+ years in software engineering or solution engineering; ~2–3+ years specifically in AI/ML or GenAI implementation.
• Bachelor’s or Master’s in Computer Science, Engineering, AI/ML, or related field.

Terms

• Location: Dallas, TX or Atlanta, GA (Hybrid).
• Duration: 3–6 months contract.
• Time commitment: approximately 3–6 hours per day.