Engineering Manager, Cloud Engineering
New
L
LaunchDarklySoftware Development
Remote - USFull-TimeManager
Salary$163,000 - $263,670 (Inclusive of a 10% Bonus Target)
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Job Details
- Experience
- 2+ years of experience managing an infrastructure, platform engineering, or site reliability engineering team
- Required Skills
- AWSKubernetesPeople Management
Requirements
- 2+ years of experience managing an infrastructure, platform engineering, or site reliability engineering team at a product company, including people management of an on-call team.
- Demonstrated ownership of incident response, on-call health, and service-level objective frameworks for critical production systems.
- Experience leading at least one multi-quarter infrastructure migration or insourcing program from planning through completion.
- Technical fluency with AWS, Kubernetes, and infrastructure-as-code practices, with the judgment to guide discussions and tradeoffs with senior engineers.
- Experience taking over an established team and maintaining engagement, performance, and retention through a leadership transition.
- A clear point of view on team norms and practices for AI-assisted engineering.
- Strong written and verbal communication skills, with the ability to explain technical and operational priorities to a range of audiences.
- A thoughtful, calm, and accountable leadership approach, particularly during incidents and periods of change.
Responsibilities
- Lead and develop a senior Cloud Engineering team, providing clear expectations, coaching, feedback, performance management, and career-development support.
- Own the operational health of LaunchDarkly’s cloud infrastructure, including incident response, on-call health, service-level objectives, resilience, and disaster recovery.
- Launch and deliver a multi-quarter infrastructure insourcing program, including sequencing work, managing dependencies, communicating milestones, and ensuring a successful transition.
- Guide technical priorities and tradeoffs across AWS infrastructure, networking, multi-region Kubernetes, infrastructure as code, GitOps, datastore operations, and compliance-related infrastructure.
- Build leverage through software, automation, and paved paths that help product engineering teams use infrastructure safely and independently.
- Support migrations by providing guidance, patterns, and enablement while maintaining clear ownership boundaries with partner teams.
- Establish team norms for effective AI-assisted engineering and identify opportunities to reduce operational toil through AI and automation.
- Maintain team health and continuity through change, fostering an inclusive, collaborative, and accountable environment.
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