Engineering Manager, Cloud Storage at Crusoe

San Francisco, California, United States

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Not SpecifiedCompensation

Senior (5 to 8 years), Expert & Leadership (9+ years)Experience Level

Full TimeJob Type

UnknownVisa

AI, Cloud Computing, EnergyIndustries

Requirements

2+ years managing or technically leading high-performing engineering teams that have built storage systems
Experience leading and growing a high-functioning team by setting goals, providing feedback, and managing performance
Capability to manage a team where problems, opportunities, and strategies may not be fully defined, driving clarity and direction
Strong ability to prioritize work, communicate trade-offs, and lead cross-functional teams through ambiguity
Clear communicator who can articulate complex technical concepts to both technical and non-technical audiences
Proven track record of delivering performance-critical products in AI, ML, or other high-performance cloud computing environments, preferably in a CSP (Cloud Service Provider), NCP (Neo-Cloud provider), or AI-infrastructure company
Familiarity with storage protocols like NFS, NVMe-oF, or S3
Motivated to remain technical with background in programming languages such as Go, C/C++, Java, Rust, and incentivized to contribute to design, architecture, and code reviews

Responsibilities

Manage and grow a team of ambitious engineers building core components of foundational storage products purpose-built for high-performance AI and ML workloads
Provide coaching, mentorship, and support for development by creating tailored career growth paths
Define clear performance expectations and career goals for the team to foster a high-performing and sustainable organization
Define engineering goals, set technical direction, and spearhead timely delivery of complex, high-visibility, and high-impact work
Collaborate with principal engineers, engineering leadership, and product to define the technical roadmap and vision for the team
Align external partner teams with the technical roadmap and develop a joint execution model with clearly defined success criteria
Provide thoughtful design inputs for architecting high-performance, scalable, and resilient storage systems
Rally the team to troubleshoot and resolve unique and complex distributed systems problems at scale
Review and understand code and provide constructive technical feedback to engineers
Foster strong collaboration across engineering teams (e.g., Software Infrastructure, Fleet Management, and SRE) and cross-functional departments like customer success, sales, and product management
Provide single-threaded ownership and representation of the storage team in business-critical initiatives across the company
Work with vendors to troubleshoot customer performance and reliability issues and iterate through the technical architecture of next-generation products

Skills

Distributed Systems

Cloud Storage

Scalable Architecture

Resilient Systems

AI Workloads

ML Workloads

Software Engineering

Code Review

Team Leadership

Technical Strategy

Crusoe

Utilizes wasted energy for computing power

About Crusoe

Crusoe Energy Systems Inc. provides digital infrastructure that focuses on using wasted, stranded, or clean energy sources to power high-performance computing and artificial intelligence. The company helps clients in the technology and energy sectors by offering scalable computing solutions that aim to reduce greenhouse gas emissions and support the transition to cleaner energy. Crusoe's approach involves converting excess natural gas and renewable energy into computing power, which allows them to maximize resource efficiency while minimizing environmental impact. Unlike many competitors, Crusoe specifically targets the intersection of energy and technology, generating revenue by supplying computing resources to enterprises that need significant computational power for applications like AI and machine learning, along with providing technical support.

Denver, ColoradoHeadquarters

2018Year Founded

$1,082.2MTotal Funding

SERIES_DCompany Stage

Energy, AI & Machine LearningIndustries

201-500Employees