Software Engineer - Fleet Management & Repair Automation

Responsibilities

• Own technical direction for a significant problem area of fleet automation – define the multi-year architecture, decide what to build, consolidate or deprecate, and drive it through to production
• Design and evolve orchestration engines: workflow modelling, scheduling and conflict resolution, execution state machines, and the contracts between our platform and the many systems that actually perform the work
• Make large-scale automation safe. Design the guardrails – unavailability budgets, rate limiting grounded in real fleet health, graceful cancellation, handbrakes, blast-radius control – for operations that physically change production capacity
• Lead through others. Decompose a broad ambiguous area into workstreams other engineers can own, review their designs, and be the technical owner the technical owner that the team's most consequential decisions route through route through
• Drive alignment across a wide cross-functional surface – capacity management, provisioning, remediation, hardware and data center operations, and external infrastructure providers. Much of the work is negotiating and formalising contracts and SLAs between systems and organisations
• Change the operating trajectory. Replace escalation paths, one-off scripts and per-case integrations with platforms and abstractions; make structural reductions in operational load rather than incremental patches
• Raise the engineering bar: mentor other engineers, set standards, and bring credible technical framing into roadmap and investment discussions

Minimum Qualifications

• BS/MS in Computer Science or equivalent practical experience
• 8+ years of professional software engineering experience, including significant time as the technical owner of a large production system
• Demonstrated staff-level scope: you have led the design and delivery of systems spanning multiple teams, across multiple planning cycles, with measurable impact
• Deep distributed systems expertise – workflow or orchestration engines, control planes, scheduling, state machines, or resource management systems
• Proficiency in one or more of Python, C++, Java, Rust or Go, demonstrated through professional experience building and maintaining production systems in one or more of Python, C++, Java, Rust or Go
• Track record of operating critical systems: oncall ownership, incident leadership, observability and SLO design, and structural reliability improvement
• Ability to lead ambiguous, cross-organisational work to completion, and to communicate clearly in writing to both engineers and senior leadership
• Experience growing other engineers through mentoring, design review and technical direction-setting

Preferred Qualifications

• Experience with constraint-based scheduling, planning or solver-backed systems
• Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
• Experience applying AI/agentic automation to operational workflows in production
• Background in infrastructure automation, fleet or capacity management, hardware lifecycle, data center operations, or cloud infrastructure
• Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
• Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
• Comfort working in a large mature codebase with heavy cross-team dependencies
• Experience building workflow/orchestration or job execution engines used by many internal customers
• Experience consolidating or deprecating legacy systems while keeping them running
• Experience integrating with heterogeneous external infrastructure APIs, including public cloud provider lifecycle and maintenance models

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