pointclickcare - (US) AI Solutions Specialist
Requirements
• AI Fluency: A solid understanding of AI/LLM concepts and the ability to translate “agentic” capabilities into practical business outcomes without requiring deep software engineering skills (AI Aptitude) • Practical experience with workflow automation and orchestration tools (n8n, Make, Zapier, or equivalent) to connect systems and automate processes without writing production code (Workflow Automation) • Analytical Fluency: Ability to interpret platform telemetry, usage data, and performance dashboards to derive actionable insights and recommendations (Analytics) • Strategic Communication: Ability to present AI outcomes and program results to internal stakeholders, framing technical capabilities in terms of business value (Communication) • Judgment about responsible AI deployment — understanding where AI adds value and where human judgment is required, especially in a regulated, customer-trust-sensitive environment (Judgment / Risk) • Ownership mindset: bias toward execution, comfort with ambiguity, and a track record of following through on initiatives end-to-end (Ownership) • Experience with CRM or Customer Success platforms (Salesforce, Gainsight, or similar) (Systems Knowledge) • Ability to work collaboratively across teams and influence without authority (Collaboration) • Bachelor’s degree, or equivalent combination of education and relevant experience (Education) • 2–4 years in Customer Success, Professional Services, support operations, or a similar customer-facing role at a SaaS or technology company (Experience) • Direct experience in a healthcare, regulated, or enterprise B2B SaaS environment with comparable scale and complexity • Hands-on experience with prompt engineering, building automations, or configuring an AI agent in a work or personal context • Experience integrating enterprise platforms (Salesforce, Gainsight, Gong, Pendo) via APIs or webhooks • Familiarity with reporting tools such as Salesforce reports, Power BI, Tableau, or Gainsight dashboards • Prior experience writing process documentation, runbooks, or playbooks for cross-functional teams • Experience navigating compliance, privacy, or regulatory constraints (HIPAA, SOC 2, or similar) • Industry domain expertise in healthcare; familiarity with EHR ecosystems, HL7/FHIR, or clinical data workflows • Experience contributing to cross-functional projects spanning Customer Success, Product, Engineering, and Operations teams • Coursework, certification, or self-directed learning in AI, data analytics, prompt engineering, or related technical fields
Responsibilities
• Identify & Execute AI Use Cases Across the Customer Lifecycle:-Identify high-impact opportunities where AI agents and automations can improve customer adoption, retention, and operational efficiency.-Design and execute AI-driven customer success programs including digital journeys, automated interventions, and agent-led workflows.-Translate business requirements into working prototypes and production-ready solutions using no-code and low-code tools, LLM APIs, and prompt engineering.-Drive continuous optimization of AI programs based on performance data and customer feedback. • Build & Maintain Workflow Automations and Platform Integrations: • Design and implement workflow orchestration pipelines using tools such as n8n, Make, Zapier, or custom-built logic layers. • Integrate AI solutions across enterprise platforms (Salesforce, Gainsight, Gong, Pendo) via APIs, webhooks, and middleware. • Manage data flows between systems, ensuring reliability and scalability of AI-driven processes without requiring engineering support for routine changes. • Prompt Engineering & AI Solution Optimization:-Develop, test, and iterate on prompt engineering strategies to maximize model accuracy, consistency, and performance.-Apply RAG (Retrieval-Augmented Generation) patterns and evaluation frameworks to improve solution quality.-Build feedback loops to continuously refine deployed AI models and agents based on real-world usage data. • Data-Driven Insights & Performance Monitoring:-Monitor AI program performance (engagement, success rates, efficiency metrics) and translate data into actionable improvements.-Instrument AI solutions with performance tracking (latency, success rates, engagement metrics, cost efficiency).-Help maintain dashboards and reports that show how AI solutions are performing; surface trends and recommendations to leadership • Cross-Functional Collaboration & AI Enablement:-Partner with Customer Success, Product, Engineering, Operations, and Enablement to embed AI into core workflows and customer engagement strategies.-Act as a subject matter expert on AI capabilities within the team — translating technical “agentic” concepts into business value for stakeholders.-Stay current on emerging AI capabilities, model releases, and agentic frameworks to drive continuous innovation across the team.
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