Systems Software Engineer — Marvis Minis & Edge AI

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

What You'll Do 

• 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  

Required Qualifications (all required) 

• 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  

Preferred Qualifications 

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 

Who Thrives Here 

• 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