Principal Engineer – AI/ML Analytics Platform

Today, there's more data and users outside the enterprise than inside, causing the network perimeter as we know it to dissolve. We realized a new perimeter was needed, one that is built in the cloud and follows and protects data wherever it goes, so we started Netskope to redefine Cloud, Network and Data Security. 

Since 2012, we have built the market-leading cloud security company and an award-winning culture powered by hundreds of employees spread across offices in Santa Clara, St. Louis, Bangalore, London, Paris, Melbourne, Taipei, and Tokyo. Our core values are openness, honesty, and transparency, and we purposely developed our open desk layouts and large meeting spaces to support and promote partnerships, collaboration, and teamwork. From catered lunches and office celebrations to employee recognition events and social professional groups such as the Awesome Women of Netskope (AWON), we strive to keep work fun, supportive and interactive.  Visit us at Netskope Careers. Please follow us on LinkedIn and .

The Opportunity

We are seeking a Principal Engineer to architect and lead the development of an advanced AI-powered analytics platform that combines machine learning, natural language interfaces, and large-scale data systems. This role is at the forefront of Netskope's innovation in cloud security intelligence, enabling our customers to derive real-time insights and automated decisions from massive volumes of telemetry and event data.

The strategic and technical leadership role requires broad systems expertise, product thinking, and a strong ability to collaborate across engineering, product, security, and AI teams. You will drive initiatives that intersect search-driven analytics (like ThoughtSpot), LLM-powered workflows (like Upsolve AI), and real-time cloud security analytics.

Key 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.

Qualifications

Core Technical Expertise

- 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).

Platform & Product Experiences

- 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.

Leadership 

- 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.

Preferred Skill Sets 

- 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.

Why Netskope

- Join a high-impact team building the future of AI-driven security intelligence

- Drive architectural decisions on next-gen analytics and ML infrastructure

- Collaborate with world-class engineers and researchers in an innovation-driven culture

- Flexible, remote-friendly workplace with a mission that matters

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