Lead the architecture and technical strategy for large-scale retrieval, ranking, vector search, RAG, and anomaly detection systems operating at enterprise scale
Drive innovation across LLMs, AI-powered discovery, personalization, and autonomous AI workflows
Define the future direction of AI-driven reasoning, ranking and investigation capabilities across the platform
Own end-to-end AI/ML architecture, including data pipelines, feature engineering, model development, deployment, monitoring, evaluation, and continuous improvement
Establish scalable architecture patterns, engineering standards, experimentation frameworks, and operational best practices across multiple teams
Drive foundational investments and technical direction across AI platforms, retrieval infrastructure, model-serving systems, and ML tooling
Balance model quality, customer experience, latency, scalability, reliability, security, and infrastructure cost when making architectural decisions
Define evaluation methodologies, experimentation strategies, and success metrics to assess product, model, and business impact
Partner closely with Product, Engineering, Security, Infrastructure, and Operations teams to identify high-value opportunities and deliver scalable AI solutions
Communicate technical trade-offs, recommendations, and results clearly to both technical and executive audiences
Lead highly ambiguous, multi-quarter initiatives spanning Product, Engineering, Data Science, and other stakeholders
Influence organization-wide technical strategy, investment priorities, and long-term AI roadmap decisions
Represent the organization in executive reviews and drive alignment on major technical and product initiatives
Mentor junior scientists while fostering a culture of technical excellence and innovation
Requirements
8+ years of experience building and scaling large-scale AI/ML, search, retrieval, ranking in the cybersecurity space
MS, PhD, or equivalent industry experience in Computer Science, Statistics, Physics, or a related quantitative discipline
Deep expertise in semantic retrieval, vector search, ranking systems, recommendation systems, NLP/LLMs, RAG architectures, and agentic AI systems
Strong understanding of retrieval and ranking trade-offs, experimentation methodologies, model evaluation, and operational excellence
Experience operating large-scale production systems with demanding latency, scalability, reliability, and cost requirements
Proven track record of delivering measurable business impact through AI and machine learning innovation
Experience leading cross-functional initiatives across multiple organizations and stakeholder groups
Ability to influence executive stakeholders and drive strategic technical decisions across large organizations
Exceptional communication, leadership, strategic thinking, and mentoring skills
Strong programming skills in Go, Python, SQL, and modern machine learning ecosystems
Experience designing and deploying end-to-end ML solutions, including data acquisition, feature engineering, model development, evaluation, deployment, and monitoring
Strong knowledge of experimentation frameworks, online evaluation, A/B testing, causal inference, and model validation methodologies
Proficiency in Anomaly Detection, MITRE entities, Detection Engineering,Triage and Investigation
Experience with modern AI infrastructure, large-scale data processing, distributed systems, and production ML platforms
Ability to communicate data-driven insights, uncertainty, assumptions, and trade-offs to technical and non-technical audiences.
Tech Stack
Cyber Security
Distributed Systems
Python
SQL
Go
Benefits
Market leader in compensation and equity awards
Comprehensive physical and mental wellness programs
Competitive vacation and holidays for recharge
Paid parental and adoption leaves
Professional development opportunities for all employees regardless of level or role
Employee Networks, geographic neighborhood groups, and volunteer opportunities to build connections