Vozy is hiring a Customer Success Engineer to own the business relationship and success outcomes for our enterprise clients. You will ensure customers achieve ROI from our voice AI platform by guiding technical implementation teams and proactively managing account health to drive retention and growth.

What You'll Do

Drive customer success and ROI by defining success metrics, tracking adoption, and ensuring clients achieve measurable business outcomes such as call automation rates, cost savings, and customer satisfaction improvements.
Manage client relationships by conducting regular check-ins, strategic reviews, and ensuring alignment between customer goals and platform capabilities.
Guide Forward Deployed Engineers by directing FDEs on client priorities, success targets, and implementation strategies to ensure technical delivery aligns with business goals.
Monitor account health by tracking usage patterns, identifying churn/downgrade risks, analyzing root causes, and developing mitigation strategies with the FDE team.
Drive expansion and upsell by identifying opportunities to expand voice AI automation across additional call types or departments.
Act as customer advocate by representing client needs internally and ensuring product roadmap addresses customer requirements.

What We're Looking For

5+ years in customer success, account management, or technical roles in SaaS.
Technical background required with previous experience as solutions engineer, implementation specialist, or similar technical role.
Familiarity with financial services, banking, or collections industry.
Strong business acumen with focus on ROI, metrics, and customer outcomes.
Experience managing churn, renewals, and account expansion.
Ability to guide technical teams while maintaining business focus.
Excellent stakeholder management and communication skills.
Native Spanish speaker with fluent English proficiency.

Nice to Have

Understanding of cloud platforms (AWS, GCP, Azure), infrastructure concepts (serverless, on premise, Kubernetes), and API architectures (REST, SOAP).
Knowledge of databases, SQL queries, and data engineering concepts (ETL pipelines).
Familiarity with data science (statistics, modeling), machine learning, and NLP concepts.
Experience with voice technologies (STT, TTS) and streaming protocols.
Background working with conversational AI or voice automation platforms.