Location
London

Hours
Full Time

Salary
Negotiable

About the Role
Fleet Management builds the automation layer for Meta's data center fleet. We own the systems that plan, orchestrate, and execute the operational workflows that keep hundreds of thousands of machines healthy, available, and efficient across every region, and increasingly across public cloud providers as well. Our platforms cover the full lifecycle of work performed on the fleet: planned maintenance and rollouts including firmware, kernel, OS, and hardware maintenance executed safely and predictably at fleet scale; unplanned work and repair including failure detection, decision making, and driving repair workflows until capacity returns to production; fleet lifecycle operations such as turn-ups, decommissions, server and service moves, rack logistics, and capacity rebalancing; safety and capacity control including managing fleet unavailability budgets, conflict resolution, rate limiting, graceful cancellation, and emergency stops; and autonomy by replacing human-driven operational decisions with automation and agentic workflows backed by observability and quality signals needed to trust them.

Practically, this means building large-scale workflow orchestration engines that model operational intent, schedule it against fleet constraints, execute it across dozens of downstream systems, and decide how to respond when steps fail. The engineering challenges involve distributed systems problems such as state machines, scheduling, conflict resolution, idempotency, partial failure, and strong safety guarantees over irreversible physical actions.

The fleet is growing rapidly, and operational volume is increasing accordingly. Our mandate is to scale fleet operations by an order of magnitude without a corresponding increase in human effort. Responsibilities include owning technical direction for significant problem areas of fleet automation by defining multi-year architecture, deciding what to build, consolidate or deprecate, and driving it through to production; designing and evolving orchestration engines including workflow modelling, scheduling, conflict resolution, execution state machines, and platform contracts; making large-scale automation safe by designing guardrails such as unavailability budgets, rate limiting grounded in real fleet health, graceful cancellation, handbrakes, and blast-radius control; leading through others by decomposing broad ambiguous areas into workstreams, reviewing designs, and being the technical owner for consequential decisions; driving alignment across cross-functional teams including capacity management, provisioning, remediation, hardware and data center operations, and external infrastructure providers; changing the operating trajectory by replacing escalation paths, one-off scripts, and per-case integrations with platforms and abstractions to achieve structural reductions in operational load; and raising the engineering bar by mentoring engineers, setting standards, and contributing credible technical framing in roadmap and investment discussions.

Experience
- 8+ years of professional software engineering experience, including significant time as the technical owner of a large production system
- Demonstrated staff-level scope with leadership in design and delivery of systems spanning multiple teams and planning cycles with measurable impact
- Deep distributed systems expertise including 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 with professional experience building and maintaining production systems
- Track record of operating critical systems including on-call ownership, incident leadership, observability and SLO design, and structural reliability improvement
- Experience leading ambiguous, cross-organizational work to completion and communicating clearly to engineers and senior leadership
- Experience growing other engineers through mentoring, design review, and technical direction-setting
- Experience with constraint-based scheduling, planning, or solver-backed systems
- Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact such as efficiency gains and 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 including risk assessment, bias mitigation, and quality and accuracy reviews
- Demonstrated ongoing AI skill development including 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 maintaining operational continuity
- Experience integrating with heterogeneous external infrastructure APIs including public cloud provider lifecycle and maintenance models

About you
You are a highly skilled software engineer with a passion for distributed systems and automation. You thrive in complex, ambiguous environments and excel at driving technical direction and alignment across diverse teams. You have strong leadership skills, enjoy mentoring others, and are committed to raising engineering standards. You are comfortable working with AI technologies and integrating them responsibly into operational workflows. You value safety, reliability, and scalability in system design and are motivated by the challenge of scaling operations without increasing human effort.

Qualifications
- BS/MS in Computer Science or equivalent practical experience