About This Role: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. 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.
What You'll Be Working On:- 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.
What You'll Bring to the Team:- 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.
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 RangeCompensation will be paid in the range of up to $190,000 - $215,000 OTE. 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.
