Customer Support Engineering Manager
Leads a team of support engineers resolving complex technical issues for enterprise AI/ML customers on Crusoe Cloud. Requires 6+ years technical experience in software/devops/support, 2+ years leadership, and deep cloud/GPU knowledge.
About the job
What You'll Be Working On
- Hire, lead and develop a team of Support Engineers focused on technical depth, problem-solving serving Crusoe's enterprise customers
- Provide thoughtful coaching and feedback to your direct reports, and partner with them on their career development goals and growth
- Build scalable, repeatable processes for diagnosing and resolving complex issues related to integrations, APIs, analytics, and product performance
- Create internal tools and workflows that help the team operate with efficiency and consistency
- Use data from escalations and customer feedback to recommend changes that improve team effectiveness and customer outcomes
- Collaborate across functions, working closely with leaders in Solutions Engineering, Customer Success and Reliability, Sales, and Product Engineering to elevate and enhance the Crusoe customer experience
- Directly engage and collaborate with key customers to understand their AI workloads, pain points, and future requirements to continuously improve our service offerings
- Define and monitor key performance indicators (KPIs) to evaluate team performance and effectiveness through leveraging multiple insights
- Communicate clearly and effectively with your team, stakeholders, and external customers
What You'll Bring to the Team
- B.S. in Computer Science or a related technical discipline, or equivalent experience with an advanced degree in a related field
- 6+ years of experience in Software Engineering, Technical Support Engineering, DevOps, Systems engineering, Solutions architecture or similar highly technical customer-facing roles
- 2+ years in a leadership role within a high-growth environment
- Deep understanding of the cloud infrastructure landscape, including fundamentals of Kubernetes, GPU compute, AI/ML, and high-performance computing
- Proven track record of successfully organizing and coordinating the efforts of multiple teams to deliver long-running, complex projects with visibility to senior stakeholders
- Passionate about improving the customer experience through well-designed, technically sound solutions
- Comfortable representing customer needs in Engineering discussions and advocating for supportability
- Expert leadership skills with the ability to influence and engage stakeholders at all levels
- Excellent verbal and written communication skills, with a strong capacity to clearly present complex technical information
- Demonstrated experience within a fast-paced, dynamic organization experiencing hypergrowth
- Experience working with global teams
Bonus Points
- Certifications: CKA, CKAD, CKS, KCNA, AWS Machine Learning - Specialty, Data Analytics - Specialty, Solutions Architect - Professional, Developer - Associate, NVIDIA AI Infrastructure and Operations, Generative AI and LLMs, Generative AI Multi-modal, Infiniband, Linux Foundation IT Associate, System Administrator
- Cloud Expertise: Deep understanding of specific cloud platforms and services
- Automation Skills: Experience with automation tools and scripting languages
- Problem-Solving Abilities: Demonstrated ability to analyze complex technical issues and develop effective solutions
- Collaboration and Mentorship: Proven ability to mentor, train, and onboard colleagues
- Passion for Sustainability: A strong interest in contributing to a more sustainable future through technology
Benefits
- Competitive compensation and equity packages
- Restricted Stock Units
- Paid time off, paid holidays & leave of absence programs
- Comprehensive health, dental & vision insurance
- Employer contributions to HSA account
- Paid parental leave
- Paid life insurance, short-term and long-term disability
- Professional development & tuition reimbursement
- Mental health & wellness support
- Commuter benefits (parking & transit)
- Cell phone stipend
- 401(k) Retirement plan with company match up to 4% of salary
- Volunteer time off
- Global travel insurance & emergency assistance
- Daily meals allowance
- Additional perks & programs specific to location
Compensation Range
Compensation will be paid in the range of up to $155,000 - $185,000 + Bonus. Restricted Stock Units are included in all offers. Compensation to be determined by the applicant's knowledge, education, and abilities, as well as internal equity and alignment with market data.
Skills
Kubernetes, Gpu Compute, AI/ML, High-Performance Computing, APIs, DevOps, Solutions Architecture, Cloud Infrastructure, Automation, Scripting
Similar jobs
Engineering Management jobsLeads commissioning programs across multiple data center projects, managing commissioning teams, third-party agents, and stakeholder coordination from pre-functional testing through turnover. Requires 10+ years of mission-critical commissioning experience, 5+ years of leadership, engineering knowledge, and a bachelor’s degree.
Leads Forge’s Site Reliability Engineering team, overseeing availability, incident response, observability, production operations, and reliability practices. Requires substantial infrastructure or software engineering experience, people leadership, and expertise with cloud platforms and operational tooling.
Leads a hands-on platform engineering team responsible for AWS infrastructure, Kubernetes deployment paths, developer self-service, CI/CD governance, reliability, and audit readiness. The role requires deep infrastructure experience, Terraform expertise, production Kubernetes operations, and people leadership.
Leads a hands-on Shared Services Engineering team building and operating reusable services, SDKs, APIs, and customer-facing systems. Requires 7+ years of software engineering experience, engineering management experience, and strong technical judgment across distributed and full-stack systems.
Leads strategy, architecture, operations, and modernization of an enterprise data platform while managing and mentoring data platform engineers. Requires 8+ years in data engineering, platforms, or architecture and experience with production cloud data systems.