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Supports SaaS client onboarding and success by preparing workflow documentation, setup templates, configuration data, and client imports. Conducts Excel-based data analysis and cleanup, writes knowledge base and process documentation, identifies operational improvements, and contributes to projects improving customer adoption, support efficiency, and performance metrics. Collaborates with Solutions Consultants and Project Managers in a remote-flexible environment.

Own end-to-end onboarding for Vantaca Pay clients, including Stripe setup, KYC compliance, portal configuration, fee and payment settings, training, and post-launch adoption. Diagnose account restrictions, resolve implementation issues, drive homeowner engagement, track 30–60 day metrics, manage escalations, maintain client relationships, and collaborate with implementation, financial services, and internal teams to improve scalable processes.

Troubleshoot, diagnose, and resolve Tier 2 SaaS support issues, including C# code, stored procedures, SQL queries, and data problems. Triage escalations, identify root causes, implement code fixes or mitigating solutions, collaborate with Product, Design, and Engineering, support customers, and maintain troubleshooting documentation.

Assist with migrating, mapping, cleaning, reconciling, and validating client financial data from legacy systems into Vantaca’s ERP platform. Create Excel reports, document migration procedures, develop workflows and checklists, and provide data accuracy insights to internal teams. The role offers hands-on experience with data transformation, client-facing projects, and SaaS operations.

The Senior Engineer will build and operate backend systems for AI agents, design APIs, optimize performance, and uphold engineering standards to ensure platform reliability and scalability.

The Forward Deployed Engineer will design, build, and deploy AI agent solutions for customers, optimize workflows, and enhance automation capabilities through active client engagement and collaboration with engineering teams.

Design, build, and maintain cloud architecture, model serving infrastructure, and ML pipelines. Optimize AI workloads for low-latency inference and cost efficiency, implement CI/CD for model deployment, monitoring, and versioning, and ensure reliability, security, and observability for mission-critical AI services. Collaborate with product and engineering teams, document runbooks, and mentor colleagues.

The Senior Backend Engineer will build and operate backend systems for AI agents, focusing on reliability, API design, and data modeling, while enhancing code quality and performance in a fast-paced environment.