Technical Solutions Engineer

Role and Responsibilities

• Provide peer-to-peer mentorship and coaching to Technical Solutions Associates, with a focus on building skills in Elation’s Developer platform and AI-powered capabilities (e.g., automation patterns, data-driven decision support).
• Serve as an internal and external subject matter expert on the capabilities of Elation’s Developer platform and AI-powered tools to support customer success, including RESTful APIs, webhooks, data warehouse access/querying, and automation services that power Clinical Insights and workflow optimization.
• Own and maintain technical workflow and sequence diagrams as reference architectures for customer integrations and common internal use cases, ensuring they are optimized for reliability, security, and scalability.
• Develop and maintain best practices, templates, and sample implementations that promote self-service, reuse, and intelligent automation where appropriate.
• Advise on and, when needed, create complex queries, reports, and data pipelines leveraging the hosted database and analytics tooling to answer strategic business and clinical questions.
• Lead or advise customer pilots and proof-of-concept implementations, including those that leverage AI to reduce manual work for clinicians and staff and demonstrate clear business and operational impact.
• Partner with customers on technical design, integrations, and product features to best utilize Elation’s platform to meet their business, technical, and delivery needs, including change management and adoption planning.
• Act as a conduit between customers and internal teams, systematically capturing technical feedback to suggest improvements across the platform, documentation, and internal tooling.
• Work cross-functionally with Product, Engineering, Data, Customer Success, Sales, and Professional Services to design and deliver data- and AI-enabled solutions that improve efficiency and time-to-value for both practices and internal teams.
• Champion a culture of experimentation and continuous improvement around AI and automation within Customer Services (e.g., identifying internal workflows that can be streamlined with AI, sharing wins and learnings, and contributing to internal AI playbooks).