GreenNode (a member of VNG Group) is a leading AI Cloud infrastructure provider, delivering a comprehensive Cloud & AI ecosystem - from Infrastructure-as-a-Service (vServer, vNetwork, vStorage) and Platform-as-a-Service (VKS - Kubernetes, vDB, vMonitor, etc.) to advanced AI Stack services (AI Platform, AI Gateway, VectorDB). Our mission is to accompany enterprises on their digital transformation journey with powerful, scalable, AI-ready Cloud-native solutions.
POSITION OVERVIEW
GreenNode is looking for a Customer Success Engineer (CSE) - a technical role within the Customer Success team, working directly with the technical teams of enterprise customers throughout their service lifecycle.
You will be the person who understands the customer's systems best from GreenNode's side: tracking how customers operate, identifying performance and cost inefficiencies, advising on solutions, and partnering with customers so they realize real value from the Cloud & AI platform - as quickly and sustainably as possible.
KEY RESPONSIBILITIES
1. Infrastructure & utilization optimization
Monitor and analyze customer service usage data (compute, storage, network, GPU) to assess operational efficiency.
Recommend performance and cost optimization measures: right-sizing, architecture adjustments, and adoption of more suitable services or features.
Track outcomes after customers adopt the recommendations and report the value delivered.
Detect early signs of abnormal usage and alert customers promptly.
2. Technical partnership & advisory
Advise on best practices for architecture, security, HA/DR and operations on the GreenNode platform.
Deliver technical training and workshops to help customer teams master their systems.
Provide in-depth support for issues beyond the Support team's scope; perform root cause analysis for recurring incidents.
Shorten the customer's Time-to-Value in bringing services into production use.
3. Periodic reviews & product roadmap
Prepare data and present the technical portion of periodic customer reviews (Monthly Review, QBR).
Introduce new features and the product roadmap, and assess their fit with each customer's use cases.
Listen to and consolidate customers' technical feedback and translate it into input for the Product team.
4. Internal collaboration & growth support
Provide technical input (sizing, scale-out architecture, new use cases) to the Sales team when customers look to expand.
Coordinate with the Support, Solution Consulting and Product teams to fully resolve customer requests.
Contribute technical content for case studies and customer success stories.
REQUIREMENT:
Must-have
3 - 5 years of experience as a Customer Success Engineer, Technical
Account Manager, Solution/System Engineer, Cloud Engineer or Technical Support (L2/L3) in Cloud, SaaS or AI/Data.
Solid knowledge of Cloud infrastructure (compute, storage, network, Kubernetes); able to read and evaluate customers' system architecture diagrams.
Proficient with monitoring/logging tools and able to analyze usage data to make optimization recommendations.
Experience working directly with enterprise (B2B) customers in an advisory or technical support role.
English: proficient in reading and understanding technical documentation
Nice-to-have
Experience with AI/ML workloads: GPU clusters, inference serving, VectorDB.
Cloud/Kubernetes certifications (CKA/CKAD, AWS/Azure/GCP).
Scripting (Python, Bash) and experience building customer-tracking reports and dashboards.
Good spoken English to work with regional customers.
Skills & Attributes
Customer-Centric: measures success by the customer's benefits and outcomes.
Proactive in spotting problems and improvement opportunities, without waiting for customers to raise them.
Consultative mindset: turns technical data into clear, valuable recommendations for customers.
Clear communicator, confident presenting to both operations teams and customer management.
Calm and methodical in incident handling; adaptable to a fast-paced, dynamic environment.
Collaborates well across teams: Support, Sales, Product and Solution Consulting.