This role has been designed as "Onsite" with an expectation that you will primarily work from an HPE office.
Hewlett Packard Enterprise is the global edge-to-cloud company advancing the way people live and work. We help companies connect, protect, analyze, and act on their data and applications wherever they live, from edge to cloud, so they can turn insights into outcomes at the speed required to thrive in today's complex world. Our culture thrives on finding new and better ways to accelerate what's next. We know varied backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs. We make bold moves, together, and are a force for good. If you are looking to stretch and grow your career our culture will embrace you. Open up opportunities with HPE.
The Opportunity
The future of networking is autonomous and AI-driven. HPE Mist Networking is building that future through Marvis Minis — a digital twin framework that runs directly on access points to continuously validate network health and feed data into our self-driving network engine.
This team owns the Minis platform end-to-end: the embedded agent, cloud data pipelines, SLE classifiers, and integrations with Marvis Actions and the Large Experience Model. You'll work across this stack — contributing to features, debugging cross-layer issues, and growing your expertise in both embedded and cloud systems.
This role will require being on site in Cupertino 2+ days a week
Develop and test Minis features across embedded (AP firmware, switches, gateways, via sandboxed test execution) and cloud (data pipelines, SLE classifiers, REST APIs)
Write and maintain Minis tests — network and application validation tests such as DNS, DHCP, ping, MTR that run on networks like APs, switches, gateways and report results to the cloud via Kafka
Debug cross-layer issues — troubleshoot problems that span AP firmware, cloud services, and data pipelines (e.g., why a downloadable mini fails on specific AP models, why SLE classifiers show incorrect data)
Contribute to cross-platform expansion — help extend Minis to switches and WAN edge devices, working with peer dev teams
Build and improve cloud services — work on Storm topologies, Airflow DAGs, Redis caching, Elasticsearch queries, and Kafka consumers that process millions of Minis test results
Participate in production operations — monitor rollouts of features and respond to customer-reported issues
Collaborate with senior engineers, the data science team, QA, and firmware teams
4+ years of professional software engineering
2+ year Go, C, or Python: This experience should be hands-on development in at least two of the following: Go, C, or Python — meaning you have written, reviewed, tested, and shipped code in these languages in a team environment, not just coursework or personal projects. You should be able to read and contribute to an existing codebase of moderate complexity in these languages.
2+ years working on Linux-based systems. Linux proficiency: Should be comfortable working in a Linux environment daily — you can write shell scripts, navigate the filesystem, use debugging tools (gdb, strace, tcpdump), manage processes, and understand file permissions and basic networking configuration (interfaces, routing, iptables).
Networking fundamentals: Understanding of TCP/IP, DNS, DHCP, and HTTP — sufficient to explain how a client obtains an IP address, resolves a hostname, and makes an HTTP request, and to interpret packet captures or traceroute output when debugging issues
1+ year of Cloud or distributed systems: experience with at least one of: message queues (Kafka, MQTT), stream processing (Storm, Flink), REST API development, or containerized deployments (Docker) — through professional work, not just tutorials
1+ year of Version control and CI/CD: Comfortable working in a Git-based workflow with pull requests, code reviews, and CI pipelines — you have used this in a team setting for at least 1 year
Education: BS in Computer Science, Electrical Engineering, or a related technical field
Experience with embedded Linux development — cross-compilation, on-device debugging, resource-constrained environments
Exposure to data pipeline tools: Apache Storm, Airflow, Redis, Elasticsearch
Familiarity with AI/ML concepts — model inference, data preprocessing, or signal processing
Experience with wireless networking, AP hardware, or IoT protocols
Experience with production monitoring, alerting, and incident response
Familiarity with Python data tools (Pandas, NumPy) or JSON data processing
Problem solvers — you dig into logs, packet captures, and code until you find the root cause
Self-starters — you take initiative and don't wait to be told what to work on next
Collaborators — you communicate clearly (especially in writing) and ask good questions
Learners — you're excited about growing across embedded and cloud, not staying in one lane
Health & Wellbeing
We strive to provide our team members and their loved ones with a comprehensive suite of benefits that supports their physical, financial and emotional wellbeing.
Personal & Professional Development
We also invest in your career because the better you are, the better we all are. We have specific programs catered to helping you reach any career goals you have — whether you want to become a knowledge expert in your field or apply your skills to another division.
Unconditional Inclusion
We are unconditionally inclusive in the way we work and celebrate individual uniqueness. We know varied backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs. We make bold moves, together, and are a force for good.