Anyscale에서 Customer Engineering 팀을 이끌 리더를 찾습니다. 분산 시스템 및 AI/ML 인프라에 대한 깊은 이해를 바탕으로 고객 기술 지원을 총괄하며, 제품 개선을 주도할 분을 모십니다. 8년 이상의 엔지니어링 경력과 3년 이상의 팀 리딩 경험이 필수입니다. 고객 중심의 기술적 문제 해결과 운영 효율화를 통해 AI 인프라의 혁신을 함께 만들어갈 분들의 많은 지원 바랍니다.
At Anyscale, we're on a mission to democratize distributed computing and make it accessible to software developers of all skill levels. We’re commercializing Ray, a popular open-source project that's creating an ecosystem of libraries for scalable machine learning. Companies like OpenAI, Uber, Spotify, Instacart, Cruise, and many more, have Ray in their tech stacks to accelerate the progress of AI applications out into the real world.
With Anyscale, we’re building the best place to run Ray, so that any developer or data scientist can scale an ML application from their laptop to the cluster without needing to be a distributed systems expert.
Proud to be backed by Andreessen Horowitz, NEA, and Addition with $250+ million raised to date.
Anyscale is looking for an experienced and hands-on engineering leader to lead our Customer Engineering team. This is a critical leadership role within our Go-To-Market organization, responsible for delivering exceptional technical support while helping ensure customer experiences directly influence the evolution of our platform.
You will lead a highly technical team responsible for supporting customers running production AI workloads on Anyscale. Your team will resolve complex technical issues, manage customer escalations, and partner closely with Product and Engineering to ensure customer feedback is translated into meaningful product improvements.
Success in this role requires balancing operational excellence with strong technical leadership. Beyond resolving individual customer issues, you will help the team identify recurring patterns, improve support workflows, expand customer self-service, and leverage automation, diagnostics, and engineering best practices to improve both the customer experience and the product over time. As opportunities arise, your team may also contribute tooling, documentation, automation, or occasional product fixes that help eliminate recurring sources of customer friction.
This role is ideal for someone who enjoys leading highly technical engineers, working closely with customers, and partnering across Engineering and Product to continuously improve how customers adopt and operate AI infrastructure at scale.
Lead a high-performing Customer Engineering team responsible for technical support, customer escalations, and technical issue resolution.
Own the operational health of the Customer Engineering team, including customer satisfaction, support quality, response times, and engineering effectiveness.
Coach and mentor a team of highly technical engineers, fostering a culture of customer focus, technical excellence, collaboration, and continuous improvement.
Build robust reporting and analytics to identify recurring customer challenges, measure operational performance, and drive continuous improvement.
Partner closely with Product Management and Engineering to communicate customer pain points, identify systemic issues, and influence product improvements based on customer feedback.
Guide the team through complex debugging, root-cause analysis, and customer escalations involving distributed systems, cloud infrastructure, and AI workloads.
Drive initiatives that reduce repeat customer issues through improved documentation, diagnostics, automation, operational improvements, and customer enablement.
Encourage the team to contribute tooling, automation, documentation, and, where appropriate, product improvements that reduce long-term customer friction.
Contribute as a key member of the Field and Customer Engineering leadership team, helping shape Anyscale's customer experience strategy.
8+ years of engineering experience, including 3–5+ years leading Support Engineering, Customer Engineering, Developer Support, Site Reliability Engineering, or related technical teams.
Experience leading customer-facing engineering teams in a high-growth SaaS or infrastructure software company.
Strong technical background with experience supporting cloud infrastructure, distributed systems, Kubernetes, AI/ML platforms, or developer infrastructure.
Demonstrated success improving the effectiveness of technical customer organizations through operational improvements, technical leadership, and strong cross-functional partnerships.
Experience partnering closely with Product Management and Engineering to communicate customer needs and influence product improvements.
Strong understanding of operational metrics and experience using data to improve customer outcomes and team performance.
Exceptional communication skills, with the ability to work effectively with customers, executives, product managers, and engineers.
Demonstrated success leading teams through complex customer escalations and technical problem solving.
Entrepreneurial mindset with a strong sense of ownership, pragmatism, and bias for execution.
You've led a Support Engineering, Customer Engineering, Developer Experience, or Site Reliability Engineering team.
You have experience contributing software, tooling, automation, or diagnostics while working in a customer-facing engineering organization.
You have experience with Ray or other distributed computing frameworks.
You have experience supporting AI/ML infrastructure or modern cloud platforms.
You've worked at a Series C or Series D startup.
You have experience working with open-source communities or partnering closely with engineering teams to improve products based on customer feedback.
Lead a talented team solving some of the most challenging technical problems in AI infrastructure and distributed computing.
Help shape how customers successfully deploy and operate AI applications at scale.
Partner closely with Product and Engineering to ensure customer feedback directly influences the evolution of the platform.
Join a collaborative engineering culture that values technical excellence, customer obsession, and continuous learning.
Be part of a high-growth company building the infrastructure powering the next generation of AI applications.
