Senior Manager, Technical Solutions & Support Engineering
H
Health Gorilla, Inc.Health tech
Remote - United StatesFull-TimeManager
Salary152,600 - 187,500 USD per year
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Job Details
- Experience
- 8+ years in technical support, support engineering, solutions engineering, technical implementation, customer engineering, or technical customer delivery for B2B SaaS, health tech, healthcare data, or enterprise software, including 3+ years leading customer-facing technical teams.
- Required Skills
- SQLSalesforceSnowflakeJiraRESTful APIsZendeskDatabricksPostmanHIPAA
Requirements
- 8+ years in technical support, support engineering, solutions engineering, technical implementation, customer engineering, or technical customer delivery for B2B SaaS, health tech, healthcare data, or enterprise software, including 3+ years leading customer-facing technical teams
- Hands-on experience troubleshooting APIs, healthcare data exchange, integrations, logs, configuration, customer environments, or production workflows
- Familiarity across FHIR, HL7, C-CDA, EHR integrations, SFTP, lab workflows, HIEs, or related infrastructure
- Demonstrated ability to build support processes, escalation paths, quality standards, ticket taxonomies, SLAs, prioritization frameworks, dashboards, and operating rhythms
- Strong judgment in distinguishing urgent from important, strategic from transactional, and support-owned from cross-functional
- Ability to translate technical complexity into clear, client-ready communication with high EQ in ambiguous, high-pressure environments
- Practical experience using AI, automation, analytics, scripting, or workflow tooling to improve support, implementation, documentation, or customer operations
- Experience with lab networks, HIEs, payer-provider data exchange, value-based care, or clinical data platforms
- Experience with SQL, Postman, API debugging, Databricks, Snowflake, Jira, Salesforce, Zendesk, Service Cloud, or similar tools
- Familiarity with HIPAA, SOC 2, PHI handling, and secure healthcare data workflows
- Experience building AI-enabled support workflows, internal agents, Markdown-based instructions, automated triage, operational monitoring, or reusable troubleshooting playbooks
Responsibilities
- Lead, coach, and develop a distributed support team, setting clear expectations for ticket quality, investigative rigor, client communication, prioritization, escalation discipline, and follow-through
- Define role clarity across front-line support, technical escalation, cross-functional support paths, and leadership coverage
- Personally engage in high-impact escalations involving APIs, HL7/FHIR/C-CDA, SFTP, patient search, query behavior, lab workflows, EHR integrations, and healthcare data exchange
- Help the team distinguish between break-fix issues, configuration problems, implementation gaps, product defects, training needs, enhancement requests, and scope or commercial questions
- Translate complex technical findings into clear, calm, client-ready updates for technical and non-technical stakeholders
- Define what Support owns and when work should route to Implementation, Product, Engineering, Solution Architecture, or Client Experience
- Create practical intake rules, handoff gates, escalation paths, severity definitions, and prioritization frameworks
- Build a business-impact-based triage model so the team prioritizes strategic clients and high-severity issues without relying on first-in-first-out or “loudest client wins” logic
- Partner with Implementation, Solution Architecture, and Client Experience to clarify warranty boundaries, post-go-live ownership, client health context, and escalation risk
- Build dashboards and operating rhythms to track ticket volume, backlog age, severity mix, response and resolution times, escalations, reopen rates, and client-level patterns
- Proactively monitor transaction volumes, shareback performance, error trends, latency, and other operational signals that may indicate client risk before a ticket escalates
- Use analytics to identify repeat issues, capacity constraints, misrouted work, and opportunities to automate, deflect, reroute, or address root causes upstream
- Lead practical AI adoption across Support, focused on triage, context retrieval, documentation, draft response support, escalation detection, and repeat-issue deflection
- Build AI-ready knowledge infrastructure: current runbooks, reusable troubleshooting workflows, structured client context, Markdown instruction files, and quality-reviewed knowledge bases
- Establish human-in-the-loop review standards so AI improves accuracy, consistency, and speed without creating client or compliance risk
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