Solutions Software Engineer

Job Summary

The Solutions Software Engineer designs, refactors, and delivers highly optimized Python and Golang automation tools to enable true model-driven infrastructure operations. Core daily duties include developing robust DevOps packages for the Ubuntu ecosystem, writing clean open source monitoring and alerting logic, troubleshooting complex virtualization, storage, and networking layers across the Linux stack, and participating in agile product sprints.

Foundational Software & Systems Prerequisites

• Python Engineering Mastery: Exceptional, professional-grade software development experience utilizing Python to build clean, maintainable, and heavily tested code packages.
• Cloud Architecture Principles: Sound, practical knowledge of distributed computing patterns, cloud resource virtualization, multi-tenant networks, and modern enterprise infrastructure concepts.
• Linux Stack Literacy: Deep structural familiarity navigating the modern Linux operating system environment, showing comfort running diagnostic tasks across networking, storage layers, and system processes.
• DevOps & Quality Mentality: A strong understanding of modern agile software development practices, highlighting a devotion to writing high-quality tests, building comprehensive documentation, and engineering for runtime stability.
• Cross-Cultural Asynchronous Agility: Superb organizational habits with a proven capability to communicate technical designs clearly and work independently within a vast, globally distributed team environment.
• Lifelong Learning Engine: A natural curiosity to routinely dive into unfamiliar software components, rethink established engineering limits, and coach peers when sharing technical breakthroughs.
• International Mobility: Willingness and regulatory flexibility to travel internationally up to 10% of the year to attend global company sprints and open source engineering events.

Preferred Technical Multipliers

• Formal Computer Science Education: A university graduate degree (BSc, MSc, or Ph.D.) in Computer Science, Software Engineering, or an equivalent technical field of study.
• Golang Programmatic Fluency: Professional or highly proficient development experience writing concurrent backend logic and infrastructure tools in Golang.
• Production Cloud Deployments: Practical, first-hand exposure managing, configuring, or debugging enterprise OpenStack private clouds or production-grade Kubernetes cluster fabrics.

Key Responsibilities

1. Model-Driven IaC Product Engineering

• Architect, implement, and optimize robust open source automation software and packages using Python and Golang to support declarative, model-driven infrastructure workflows.
• Create and refine next-generation infrastructure-as-code patterns designed to streamline bare-metal operations, high-performance computing configurations, data lakes, and AI/ML pipelines.
• Ensure all developed automation modules maintain elite quality standards across architectural design, performance benchmarks, and overall platform reliability.

2. Full-Stack Linux & Core Telemetry Evolution

• Work confidently across the entire Linux operating system stack, debugging performance issues spanning the kernel boundary, local software storage pools, hypervisors, and container runtimes.
• Build, upgrade, and maintain highly reliable, low-overhead open source monitoring, metrics collection, and system alerting infrastructure.
• Review real-world operational issues alongside Canonical's managed infrastructure teams, transforming active system bugs into permanent automation fixes in the open source code.

3. Collaborative Knowledge Sharing & Agile Practice

• Engage actively in standard agile software ceremonies, contributing deeply to codebase peer reviews, feature estimation loops, and system documentation.
• Provide technical guidance, code reviews, and mentorship to global team colleagues to spread engineering best practices.
• Help cultivate a healthy, zero-politics, and execution-focused team culture aligned with Canonical's open source product vision.

Core Competencies & Infrastructure Engineering Strengths

• Declarative System State Modeling: Deep technical insight into building automation scripts that enforce predictable system states across hardware clusters without manual steps.
• Network Telemetry Diagnosis: Fluent understanding of Linux network configurations, bridging systems, virtual routing patterns, and enterprise packet flow mapping.
• Algorithmic Data Processing: The software capability to construct elegant, highly performant Python code that parses complex server states, handles heavy configuration structures, and interfaces smoothly with system APIs.
• Uncompromising Code Discipline: A strict dedication to test-driven development metrics, continuous validation pipelines, and transparent, self-documenting code.
• Asynchronous Collaboration Presence: Excellent technical writing and conversational English skills, ensuring your design pitches and pull requests are understood across multiple global time zones.

Skills Required:

• Computer / Software / It / Data