Director of Data Science - AI Engineering (Remote, ROU)

Undelucram.ro on behalf of: Crowdstrike SRLAbout the Role: CrowdStrike is seeking an exceptional Director of Data Science to partner specifically with our Charlotte AI and GenAI Platform engineering teams. As the Director of Data Science for AI Engineering, you will work with the Charlotte AI engineering team to research and optimize large language models for cybersecurity-specific natural language processing, threat analysis, and automated response generation. Simultaneously, you will collaborate with the GenAI Platform engineering team to build the foundational ML infrastructure that supports internal and external GenAI applications. What You'll Do:

• Lead data science for flagship AI products that are transforming cybersecurity operations globally
• Work on technology that processes security data for Fortune 100 companies and thousands of security professionals
• Shape the future of AI-driven security solutions that materially reduce cyber risk for organizations worldwide
• Gain deep expertise in applying LLMs and distributed systems at enterprise scale in a high-impact, customer-facing context
• Join a role that sits at the forefront of AI in cybersecurity, defining how AI will be adopted in enterprises to combat threats

Key ResponsibilitiesStrategic Partnership & Leadership

• Partner specifically with Charlotte AI and GenAI Platform Engineering leaders to define integrated roadmaps
• Collaborate with Charlotte AI team on optimizing transformer models for cybersecurity-specific NLP tasks
• Work closely with GenAI Platform engineering to align vector database, RAG systems, and LLM serving infrastructure with Charlotte AI's conversational AI requirements
• Co-develop LLM fine-tuning, prompt engineering, and model evaluation standards specifically for Charlotte AI and GenAI Platform teams

Charlotte AI Collaborative Development

• Partner directly with engineering teams to integrate LLM-based conversational AI models into the threat detection and triage pipeline, distinct from traditional ML models in Falcon
• Collaborate with product engineers to implement real-time LLM inference for natural language threat analysis and automated response generation
• Work alongside backend teams to optimize transformer model performance for cybersecurity-specific reasoning tasks
• Co-design with frontend engineers to ensure conversational AI interactions and LLM-generated insights are effectively presented to security analysts
• Partner with engineering teams to establish robust LLM deployment pipelines, prompt versioning, and model monitoring workflows specific to generative AI
• Collaborate on achieving and maintaining >98% accuracy in threat detection conversations and automated triage recommendations

GenAI Platform Engineering Collaboration

• Partner with infrastructure teams to co-design LLM serving architecture, vector database systems, and RAG pipelines for conversational AI and agentic workflows
• Collaborate with platform engineers to build shared LLM fine-tuning and evaluation frameworks that serve multiple AI applications including conversational AI, internal tooling and coding assistants
• Work closely with cost optimization teams to implement intelligent LLM routing across multiple providers and custom models
• Partner with observability engineers to design comprehensive LLM monitoring, token usage tracking, and generative AI performance alerting systems
• Collaborate with data engineering teams to build robust vector database integrations for cybersecurity knowledge retrieval and context augmentation
• Co-develop with platform teams the shared generative AI infrastructure that powers conversational AI, agentic workflows, and internal AI tooling

Collaborative Team Leadership

• Build and lead a specialized data science team focused exclusively on LLM research, prompt engineering, and generative AI applications for cybersecurity - embedded with Charlotte AI and GenAI Platform engineering teams
• Foster deep collaboration between LLM researchers and AI engineers through shared OKRs, and cross-functional mentoring
• Create integrated development processes where data scientists and engineers collaborate on LLM fine-tuning, prompt optimization, RAG system development, and agentic AI workflows

Technical Excellence & Innovation

• Stay at the forefront of AI/ML research, particularly in areas relevant to cybersecurity
• Drive adoption of state-of-the-art techniques in large language models, multimodal AI, and agentic systems
• Establish rigorous experimentation frameworks and A/B testing methodologies
• Ensure responsible AI practices, including bias detection, fairness, and explainability
• Lead efforts in model security, adversarial robustness, and AI safety

Impact You'll Drive

• Optimize systems that eliminate 40+ hours of manual work per week for customers
• Enhance AI capabilities that speed up security inquiries by 75% and boost analyst efficiency by 52%
• Scale AI infrastructure serving 8,000+ internal employees across engineering, sales, marketing, and HR
• Drive technology that processes thousands of daily queries improving productivity and decision-making

Products You'll Impact

• Charlotte AI: Industry-first conversational AI security analyst that converts hours of work into minutes, with agentic response capabilities recognized as among 2025's hottest cybersecurity products
• GenAI Hub & GenAI Platform: Enterprise-grade AI infrastructure democratizing cutting-edge AI access across 10,000+ employees while maintaining security and reliability

What You'll Need:Education & Experience

• PhD in Computer Science, Machine Learning, Statistics, or related quantitative field, OR
• Master's degree with 8+ years of relevant industry experience
• 5+ years of experience leading data science teams in production environments
• 3+ years of experience with large language models, generative AI, or related technologies

Technical Expertise

• Deep expertise in machine learning, deep learning, and statistical modeling
• Extensive experience with LLMs, transformer architectures, and generative AI techniques
• Proficiency in Python, R, or similar languages for data science and ML
• Experience with ML frameworks (PyTorch, TensorFlow, Hugging Face, etc.)
• Strong background in MLOps, model deployment, and production ML systems
• Experience with cloud platforms (AWS, Azure, GCP) and distributed computing
• Knowledge of vector databases, embedding models, and RAG architectures

Team Culture & Collaborative LeadershipCollaborative Leadership & Communication

• Lead within a startup mindset inside a global cybersecurity leader
• Partner with teams that operate with complete autonomy and end-to-end ownership
• Collaborate with cross-functional units including dedicated product managers, UX designers, and security strategists
• Work in a culture of innovation, mentorship, and continuous learning with rapid experimentation and release cycles
• Lead integrated teams where every voice is heard and every member contributes to both technical and strategic direction
• Foster collaboration across Romania (primary hub), Europe, and expanding US presence Proven experience leading data science teams in close partnership with engineering organizations
• Track record of successful collaboration with engineering directors and technical leads on complex AI/ML initiatives
• Strong ability to facilitate technical discussions between data science and engineering teams, driving consensus on architectural decisions
• Experience co-presenting technical roadmaps and results with engineering partners to executive leadership
• Demonstrated success in building integrated data science-engineering workflows that deliver production AI systems at scale

Preferred QualificationsDomain Expertise

• Experience in cybersecurity, threat detection, or security analytics
• Background in anomaly detection, fraud detection, or similar security-adjacent domains
• Knowledge of cybersecurity frameworks, threat intelligence, and security operations
• Experience with time-series analysis, log analysis, or security event correlation

Advanced Technical Skills

• Experience with agentic AI systems, multi-agent frameworks, or autonomous systems
• Background in reinforcement learning, particularly for decision-making systems
• Experience with model interpretability, explainable AI, and responsible AI practices
• Knowledge of federated learning, privacy-preserving ML, or secure computation
• Experience with real-time ML systems and low-latency inference

Industry Experience

• Previous experience leading data science teams focused on LLM applications, generative AI, or conversational AI systems in close collaboration with engineering organizations
• Track record of partnering with engineering teams to deliver enterprise B2B generative AI products, LLM-powered customer-facing systems, or agentic AI workflows
• Background in collaborative development of LLM-based AI products that operate at scale, with specific experience in vector databases, RAG systems, and LLM serving infrastructure
• Experience in organizations where generative AI data science and engineering teams work as integrated units to deliver production LLM capabilities, distinct from traditional ML model development