Netskope (NASDAQ: NTSK) is a leader in modern security and networking for the cloud and AI era. We secure and accelerate cloud, data, and AI in real time, everywhere. Thousands of customers, including more than 30 of the Fortune 100, trust the Netskope One platform, its Zero Trust Engine, and the powerful NewEdge network to gain full visibility and control without performance trade-offs.
At Netskope, our technology is driven by our greatest strength: our people. We believe that belonging powers innovation, and success is both personal and organizational. We embrace differences in gender, ethnicity, beliefs, ability, and identity, creating an environment where every voice is heard and respected. We empower our employees to bring their authentic selves to work, grow their careers through continuous education and mentorship, and lead with transparency and curiosity. Join a team where you belong, where you are encouraged to be an entrepreneur, and where together, we continue to redefine the landscape of security.
Visit Careers at Netskope to learn more. Follow us on LinkedIn and Instagram.
About the role
Please note, this team is hiring across all levels and candidates are individually assessed and appropriately leveled based upon their skills and experience.
Netskope's Data Platform is the backbone behind every security insight our customers see, ingesting and processing security telemetry from a global edge network at massive scale. We own the full data path — from collection at the edge, through stream processing and enrichment, to the query, routing, and delivery systems that put that data in customers' hands. On top of that foundation we build the analytics, reporting, and export capabilities that our customers rely on to understand and act on their security posture. We are now investing in an AI-native future, building a semantic layer that makes our data machine-interpretable and agentic experiences that let customers ask questions of their data in natural language.
What you’ll work on
- Partner with architects to design and evolve the systems that carry telemetry from global edge ingestion through processing, query, and customer delivery, with a focus on scale, durability & latency.
- Raise the bar on observability, SLOs, deployment safety, and production resilience of the platform that others build on top of - not just a single service.
- Build the AI-native semantic layer that’s the foundation to make our data machine-interpretable, and the agentic experiences on top of it that let customers ask questions in natural language.
- Lead cross-team initiatives, shaping architecture through design reviews, and mentoring engineers, with the freedom to adopt modern & open source technologies.
Required skills and experience
- 10+ years building and operating large-scale distributed systems, with significant time operating at Staff-level (or equivalent) technical scope.
- Strong coding ability in one or more of Go, Java, Python, or C++, with a track record of shipping production systems, not just designing them.
- Experience designing for reliability at scale — observability, SLOs, incident response, and safe deployment on cloud infrastructure (AWS/GCP, Kubernetes).
- Demonstrated cross-team technical leadership: influencing architecture decisions, driving design decisions, and aligning teams around a direction.
- Experience building high-throughput ingestion and data services over modern RPC and wire protocols — HTTP/2, gRPC, and Protocol Buffers — including schema design and evolution.
- Experience with high-throughput data pipelines — data streaming & batch ingestion, processing, and storage using columnar data formats such as Parquet
- Excellent written and verbal communication, and the flexibility to collaborate across time zones with globally distributed teams.
- Ability to ramp up quickly into unfamiliar codebases and domains as priorities evolve, mentoring engineers and raising the engineering bar around you.
- Familiarity with, or strong interest in, LLM-based systems, semantic layers, or data modeling for AI applications.
Education
- BSCS or equivalent required, MSCS or equivalent strongly preferred
Netskope is committed to implementing equal employment opportunities for all employees and applicants for employment. Netskope does not discriminate in employment opportunities or practices based on religion, race, color, sex, marital or veteran statues, age, national origin, ancestry, physical or mental disability, medical condition, sexual orientation, gender identity/expression, genetic information, pregnancy (including childbirth, lactation and related medical conditions), or any other characteristic protected by the laws or regulations of any jurisdiction in which we operate.
Netskope respects your privacy and is committed to protecting the personal information you share with us, please refer to Netskope's Privacy Policy for more details.
The application window for this position is expected to close within 50 days. You may apply by filling out the below information, or visiting our Netskope Careers site.
Skills Required
- 10+ years building and operating large-scale distributed systems, including significant Staff-level or equivalent technical scope
- Strong coding ability in one or more of Go, Java, Python, or C++, with experience shipping production systems
- Experience designing for reliability at scale, including observability, SLOs, incident response, and safe deployment on AWS or GCP and Kubernetes
- Demonstrated cross-team technical leadership, including influencing architecture, driving design decisions, and aligning teams
- Experience building high-throughput ingestion and data services using HTTP/2, gRPC, Protocol Buffers, and schema design and evolution
- Experience with high-throughput streaming and batch data pipelines, processing, and storage using columnar formats such as Parquet
- Excellent written and verbal communication and ability to collaborate across time zones with globally distributed teams
- Ability to ramp up quickly in unfamiliar codebases and domains, mentor engineers, and raise engineering standards
- Familiarity with or strong interest in LLM-based systems, semantic layers, or data modeling for AI applications
- Bachelor’s degree in computer science or equivalent
- Master’s degree in computer science or equivalent
Netskope Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Netskope and has not been reviewed or approved by Netskope.
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Fair & Transparent Compensation — Pay is considered competitive in U.S. technical roles, with indications that total compensation benchmarks strongly versus peers. Employees are generally pleased with total compensation that includes pay, stock, equity, and benefits.
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Healthcare Strength — Health coverage offers multiple medical plan choices alongside dental, vision, disability, HSA/FSA, and EAP, and is often characterized as very good. Employer-verified plan options and regional choices reinforce the breadth and quality of coverage.
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Leave & Time Off Breadth — Time off includes flexible/unlimited PTO, paid holidays, and quarterly wellness days that support rest and flexibility. Paid parental leave is available, commonly cited at 12 weeks for birth parents and 8 weeks for non‑birth parents.
Netskope Insights
What We Do
Netskope, the SASE leader, safely and quickly connects users directly to the internet, any application, and their infrastructure from any device, on or off the network. With CASB, SWG, and ZTNA built natively in a single platform, the Netskope Security Cloud provides the most granular context, via patented technology, to enable conditional access and user awareness while enforcing zero trust principles across data protection and threat prevention everywhere. Unlike others who force tradeoffs between security and networking, Netskope’s global security private cloud provides full compute capabilities at the edge. Netskope is fast everywhere, data-centric, and cloud-smart, all while enabling good digital citizenship and providing a lower total-cost-of-ownership.
