Principal Engineer

Summary

Join Netskope's high-impact team and build the future of AI-driven security intelligence. As a Principal Engineer, you will architect and lead the development of an advanced AI-powered analytics platform. This platform will combine machine learning, natural language interfaces, and large-scale data systems, enabling real-time insights and automated decisions from massive volumes of data. You will drive initiatives intersecting search-driven analytics, LLM-powered workflows, and real-time cloud security analytics. This strategic and technical leadership role demands broad systems expertise, product thinking, and strong collaboration skills across various teams. You will define architectural direction, mentor senior engineers, and represent the engineering vision in cross-functional discussions.

Requirements

• 15+ years of experience building scalable, distributed systems for data analytics, ML, or search-based platforms
• Proven track record of architecting and delivering end-to-end AI or analytics platforms (BI tools, data apps, or ML-driven insights platforms)
• Deep expertise in backend engineering using Python, Java, or Scala; advanced proficiency in SQL and performance optimization
• Experience designing streaming and batch data pipelines using tools like Spark, Kafka, Flink, or equivalent
• Hands-on experience with MLOps platforms and modern ML deployment workflows (e.g., MLflow, Kubeflow, Airflow)
• Strong understanding of LLMs and vector databases (e.g., Pinecone, PGVector) and their application in semantic search and insight generation
• Deep understanding of data modeling for analytical systems (star/snowflake schemas, OLAP, dimensional modeling)
• Demonstrated success in building platforms that power user-facing experiences like dashboards, alerts, or search interfaces (e.g., ThoughtSpot, Looker, or similar)
• Experience working with modern cloud platforms (AWS, GCP, Azure) and big data storage engines (BigQuery, ClickHouse, Snowflake)
• Proven ability to balance technical depth with product intuition—able to align platform direction with user value and business goals
• Exceptional communication and collaboration skills across functions—engineering, product, data science, and executive stakeholders
• Ability to define and influence architectural direction at an organizational level
• Experience mentoring staff- and senior-level engineers and setting long-term engineering strategies

Responsibilities

• Define and drive the architecture for an AI analytics platform that supports natural language queries, visual analytics, and ML-assisted insights across security data
• Lead the integration of LLMs and Retrieval-Augmented Generation (RAG) into interactive analytics flows, enabling context-rich user experiences
• Own the design and development of high-performance data systems for querying, indexing, and streaming large-scale telemetry and behavioral data
• Drive backend platform scalability, availability, and observability across core analytics and ML services
• Partner with security, data science, and product teams to prioritize use cases, define technical strategy, and influence roadmap
• Establish engineering best practices in system design, API architecture, performance tuning, data modeling, and ML platform integration
• Mentor senior engineers and foster a high-bar engineering culture grounded in innovation, ownership, and execution
• Represent the engineering vision in cross-functional strategy discussions, architectural reviews, and external technical forums if needed

Preferred Qualifications

• Prior experience in security analytics, threat detection, or operationalizing security data at scale
• Exposure to natural language query systems or AI copilots (e.g., NL2SQL, prompt engineering, question-answering)
• Contributions to open-source platforms in analytics, AI infrastructure, or LLM tools

Benefits

Flexible, remote-friendly workplace