Senior Customer Success Manager, Crusoe Energy Systems
Managed Inference
$190-215k
OTE
Plus equity
Renewable-powered AI infrastructure
Be an early applicant
Renewable-powered AI infrastructure
1001+ employees
Be an early applicant
$190-215k
OTE
Plus equity
1001+ employees
Company mission
To accelerate the abundance of energy and intelligence.
Role
Who you are
- We're looking for problem-solving, opportunity-finding teammates with a sense of urgency, who believe in the scale of our ambition and thrive on a path not fully paved — people who want to grow their careers alongside a team of experts across energy, manufacturing, data center construction, and cloud services
- We are seeking a highly motivated and skilled Senior Customer Success Manager with a strong background in customer engagement and a deep technical understanding of cloud computing, AI, and ML
- The ideal candidate has experience supporting customers running production AI inference workloads and understands the operational, technical, and business challenges associated with deploying and scaling AI applications
- Experience supporting Managed Inference, model serving platforms, LLM deployments, AI agents, or GPU-based inference environments is highly preferred
- Educational Background: Bachelor’s degree in Business, Engineering, or a related field. Advanced degree preferred
- Professional Experience: Proven experience in customer success, technical account management, or a similar role in a technology-driven environment
- 3+ years of experience supporting enterprise cloud, AI, machine learning, developer platform, or infrastructure customers
- Experience managing strategic accounts running production AI workloads is strongly preferred
- Technical Proficiency: Strong technical foundation in cloud computing platforms, AI, and ML technologies, with the ability to communicate complex concepts in simple terms
- Strong understanding of inference workloads, model serving architectures, Kubernetes, containers, APIs, GPU infrastructure, and AI application deployment patterns
- Familiarity with LLMs, RAG architectures, agentic applications, model performance metrics, and inference optimization concepts is highly desirable
- Interpersonal Skills: Excellent interpersonal, communication, and presentation skills
- Relationship Building: Demonstrated ability to build relationships at all levels within an organization
- Ability to engage effectively with both executive stakeholders and deeply technical customer teams, including AI Engineers, ML Engineers, Platform Engineers, and Infrastructure leaders
- Adaptability: Comfortable working in a fast-paced environment with ambiguous and/or iterative fact-sets
What the job involves
- This role is pivotal in ensuring that our clients maximize the value of our solutions, guiding them through the technical complexities and empowering them with the tools and knowledge to achieve their business and sustainability goals. This is a full-time position
- Customer Relationship Management: Develop and maintain strong, long-lasting customer relationships, understanding their business needs and technical requirements
- Own strategic relationships with AI-native customers deploying production inference workloads, helping them achieve performance, reliability, latency, scalability, and cost optimization objectives
- Customer Advocacy: Work on case studies to highlight customer successes
- Technical Liaison: Act as the bridge between our clients and our technical team, ensuring clear communication and alignment of goals
- Technical Guidance and Support: Provide technical guidance and support to customers in the implementation and optimization of our cloud-based AI and ML solutions including Kubernetes solutions
- Partner with customers on model deployment strategies, inference optimization, GPU utilization, autoscaling, throughput management, observability, and production readiness best practices
- Performance Monitoring and Reporting: Conduct regular reviews and report on customer progress, ensuring the achievement of key performance indicators and return on investment
- Monitor customer adoption, inference consumption trends, latency metrics, uptime, capacity utilization, and business outcomes to identify growth opportunities and potential risks
- Customer Journey Coordination: Coordinate with the product and engineering teams to define customer journeys, challenges, and opportunities
- Partner closely with Product, Engineering, CS, and Solutions teams to advocate for customer needs and influence roadmap priorities related to inference platforms and AI services
- Industry and Technical Awareness: Stay up-to-date with industry trends, technical advancements, and regulatory changes to provide strategic advice to clients
- Maintain a strong understanding of emerging AI technologies, LLMs, model serving architectures, agentic workflows, inference optimization techniques, and GPU infrastructure trends
- Customer Training: Deliver training sessions and workshops to customers on the use and benefits of our products and services
- Issue Resolution: Address and resolve customer concerns, ensuring high levels of customer satisfaction and retention
- Act as a trusted advisor during customer escalations, service incidents, and critical production events, helping customers navigate complex technical and business challenges
Our take
Crusoe is tackling one of the biggest challenges facing the digital age: the enormous energy demand of data centres and AI infrastructure. As AI models grow more powerful, they require immense computing power (and therefor electricity) to train and operate. This surge in energy use has put some pressure on power grids, driven up costs, and raised environmental concerns. Crusoe is on a mission to make this process more sustainable by finding smarter, cleaner, and more efficient ways to power the data centres that drive modern computing.
The company started out by putting wasted energy to work. Originally known as Crusoe Energy, it captured natural gas that would otherwise be burned off ("flared") at remote oil sites and used it to power modular data centres. Today, Crusoe has evolved into a major player in AI infrastructure, designing and operating large-scale data centres near renewable or stranded energy sources. It's now one of a handful of "neocloud" companies (next-generation cloud providers focused on flexible, efficient computing for AI workloads). And its facilities are helping tech giants like OpenAI handle the massive computing requirements of training advanced AI models.
Recently, Crusoe has attracted some huge investor attention, tripling its valuation to over $10B and raising almost $1.4B in its 2025 funding round. It's building OpenAI's first major US data centre campus and even experimenting with bold new frontiers. In partnership with Starcloud, Crusoe plans to deploy the world's first space-based cloud computing infrastructure, powered by solar energy and orbiting the Earth by 2027. If successful, this could redefine how and where computing happens, opening up a cleaner, virtually limitless source of energy for AI's next generation.
Steph
Company Specialist at Welcome to the Jungle
Company
Funding (last 2 of 6 rounds)
Oct 2025
$1.4bn
SERIES E
Dec 2024
$600m
SERIES D
Total funding: $2.5bn
Company benefits
- Health & wellbeing: Comprehensive health benefits designed to support your overall wellness
- Time away: Paid time off for vacations, family bonding, and unexpected needs
- 401(k) match: Build your financial future with our 401(k) matching program
- Mental wellness: Resources and support for your emotional wellbeing and navigating life's challenges
Company HQ
Union Station, Denver, CO
Leadership
Cully Cavness
(Co-Founder, COO & President)Began their career as an Energy Infrastructure Research Fellow before spending 3 years as a Business Development Manager at Recurrent Engineering and serving as CFO of Sword & Plough. They left their role as VP of Highlands Natural Resources to co-found Crusoe Energy Systems.
Chase Lochmiller
(Co-Founder & CEO)Prior to co-founding Crusoe in 2018, Chase was a General Partner at Polychain Capital, a Quantitative Trade at Jump Trading Group, and a Managing Director of Algorithmic Trading at KCG Holdings.
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