Customer Success Engineer – Analytics as a Service
Raliant· enterprise· Jul 22, 2026 · 3mo agoPosted 97 days ago
Fairport, NY, United States
In office
Full-time
Staff
$176K–$245K est.
8+ years exp
Before you apply
Ghost Signal:
Open since July 22, 2026 — 97 days, and still accepting applications.
Job description
Customer Success Engineer – Analytics as a Service
Position Summary
The Customer Success Engineer owns the complete customer journey from signed order through deployment, adoption, measurable customer outcomes, renewal and expansion.
This role combines technical implementation, DevOps coordination, customer consulting and AI-enabled process design. The objective is to create a highly scalable customer success operating model capable of supporting a rapidly growing global SaaS business with minimal additional resources.
This position is equally responsible for ensuring customer value realization and continuously improving the product through structured Voice of Customer feedback loops.
Primary Responsibilities
Customer Journey Ownership
Own the complete lifecycle: Order, Planning, Data Integration, Deployment, Validation, Training, Adoption, Value Realization, Expansion and Renewal.
Customer Success Playbooks
Develop standardized workflows for:
• onboarding
• implementation
• customer reviews
• renewal planning
• expansion opportunities
• executive reporting
Service Deployment
Lead deployment of two analytics services and expand into future ones.
Coordinate with:
• DevOps
• Product Owner
• Engineering
• Sales
• Customer IT organizations
Voice of Customer
Partner with the Product Owner and Product Manager to establish structured VOC processes including:
• Follow Me Home visits
• Customer Advisory Boards
• Early Adopter Councils
• Customer health scoring
• Usage analytics
• Translate customer insights directly into prioritized product improvements
Service Reliability
Partner closely with DevOps to:
• monitor service health
• improve uptime
• reduce deployment effort
• automate provisioning
• automate monitoring
• improve operational maturity
AI-enabled Scaling
Develop AI-powered customer success capabilities including:
• automated onboarding
• AI knowledge assistants
• customer self-service
• deployment automation
• health score prediction
• proactive support
• AI-generated customer reports
• automated documentation
• workflow orchestration
Customer Value Realization
Ensure every customer receives measurable business outcomes through:
• adoption tracking
• KPI dashboards
• ROI reporting
• executive value reviews
• success plans
Required Experience
• 8+ years industrial software deployment
• Experience with SaaS, Networking and Cybersecurity implementation issues
• Experience with cloud platforms
• Experience managing enterprise customers
• Strong project leadership
• Excellent customer communication
• Experience working alongside software engineering organizations
Preferred Experience
Industrial domains including:
• Utilities
• Power systems
• Asset monitoring
• Industrial IoT
• Digital services
Success Measures
Within 12 months:
• Standardized deployment methodology established
• Deployment time reduced significantly
• Customer onboarding largely automated
• Strong renewal readiness across install base
• Product feedback loops operating continuously
• Successful deployment of all targeted pilot and paid projects
Travel
Approximately 30–40% domestic and international travel
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Keywords to mirror
ai
- Platform
- oracle-cloud
- Effort
- medium
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