The Juniper Mist solution is set to transform IT with AI-driven operations and support; assure the best wireless LAN, wired LAN, and SD-WAN experiences with unprecedented scale, agility, resiliency and performance; revolutionize antiquated architectures that traditional solutions are built on; and address today’s diverse enterprise needs.


Juniper Mist solves this with a combination of artificial intelligence, machine learning, and data science techniques, a revolutionary approach to leverage AI-driven automation and insight, coupled with the agility and reliability of a microservices cloud to deliver optimized experiences and simplified network operations. Data is ingested from numerous sources, including Juniper Mist Access Points, Switches, and Firewalls for end-to-end insight into user experiences. These devices work in concert with Mist AI to optimize user experiences from client-to-cloud, including automated event correlation, root cause identification, Self-Driving Network™ operations, network assurance, proactive anomaly detection, and more. Now IT teams can streamline operations and simplify user and device troubleshooting across the wireless access, wired access, and SD-WAN domains.



Overview

The Engineer I - Multidisciplinary track is a fresh program at Juniper Mist Engineering department specifically designed for entry level engineers. The candidate, once hired, will work on multiple projects across different engineering fields: software development, DevOps, quality assurance, etc., and then match with a team. This position allows the prospect to first build a comprehensive view of modern, complex organic cloud AI systems before diving into a specialty.



Responsibilities

Work with mentors to complete engineering coding projects in the given timeframe.
Example projects may include (but not limited to):
Automate internal processes to simplify engineering operations
Design test plans and automate test cases for continuous end-to-end coverage
Understand the Mist UI and API architecture to be able to fix and improve the current design
Develop backend software that runs on AWS and GCP public clouds to manage and monitor network devices
Utilize APIs to develop tools to maintain/monitor the production cloud systems – SQL/NoSQL/Streaming/Batch pipeline
Develop real-time data pipeline using Flink and Apache Storm Topology and batch processing using Spark jobs
Build and deploy tools to drive massive scale cloud
Present project results to the team


Qualifications

Degree in Computer Science or a related field