Staff Technical Account Manager

The Staff Technical Account Manager is responsible is a critical member of Avalara’s support organization, responsible for managing technical tickets, ensuring timely resolution, and driving customer satisfaction for our Enterprise. Involving complex product and connector issues that cannot be fully resolved through frontline troubleshooting alone, while improving the speed, quality, and consistency of engineering engagement. This is an engineering-aligned support talent that can reduce time to resolution, improve case quality, raise the standard of Jira submissions, and turn repeat issues into durable knowledge and process improvements. It also reflects Avalara’s broader need to embed AI into technical support in practical ways that improve investigation speed, communication quality, and team scalability. In addition to resolving complex issues, this role is expected to use AI in day-to-day work to accelerate research, strengthen technical analysis, improve case documentation, and identify opportunities to make technical support more effective and scalable over time. The business outcome this role enables is straightforward: better customer experience, faster and more reliable resolution of complex cases, better use of engineering capacity, stronger support scalability, and fewer repeat incidents over time. By combining technical judgment with thoughtful AI adoption, this role also helps Avalara improve how support work is performed, not just how individual cases are resolved. How This Role Elevates Avalara This role raises the technical bar of Enterprise Support by bringing stronger investigation discipline, better case documentation, cleaner handoffs, more effective Jira creation, and clearer collaboration with Product and Engineering. It also improves the capability of the broader support organization by turning difficult cases into reusable knowledge, troubleshooting actions, and support-ready guidance that reduces future rework. This role helps Avalara reduce unnecessary Jira volume, improve the quality of engineering escalations, and protect engineering capacity for the issues that truly require development effort. It also supports better operational performance through stronger SLA discipline, cleaner milestone adherence, faster TTR, and more predictable case outcomes. This role improves customer trust by ensuring that the most complex issues are handled with technical depth, clear communication, accurate diagnosis, and accountable resolution ownership. It also improves the long-term customer experience by reducing repeat incidents and strengthening self-service through better knowledge assets and preventative actions. Protect and increase Enterprise customer revenue and retention by resolving complex customer-impacting issues quickly and accurately. For customers, the TAM provides a trusted technical partner who understands their environment, anticipates risk, and delivers clarity during high-impact situations. This proactive, relationship-driven approach increases platform reliability, improves customer experience, and drives long-term success What Your Responsibilities Will Be Provide leadership and mentorship to TAMs – providing knowledge sessions, brown-bag training and advanced troubleshooting of APIs and ERPs. Own a portfolio of Avalara’s Enterprise customers with premium support entitlement. Own complex support cases from assignment through verified resolution, especially where advanced troubleshooting, reproduction, deep product analysis, or engineering coordination is required. Perform advanced troubleshooting and root cause analysis across ERP/CRM/eCommerce platforms (NetSuite, D365, SAP, Oracle, Salesforce, Shopify, Workday, etc.). Diagnose customer issues across AvaTax, connectors, and related workflows by reproducing issues, gathering diagnostics, isolating scope, documenting findings, and confirming business impact. Determine when engineering involvement is warranted and ensure Jira tickets are necessary, complete, technically credible, and supported by strong due diligence before submission. Create, refine, and manage Jira tickets that clearly describe the issue, expected and actual behaviour, troubleshooting completed, reproduction detail, supporting evidence, and urgency. Partner closely with Product and Engineering to drive defect resolution, maintain momentum on linked development work, and keep customer cases moving while internal work is in progress. Maintain strong customer communication discipline by meeting milestone expectations, providing proactive updates, responding quickly to new customer messages, and keeping status and documentation audit ready. Improve support effectiveness beyond the individual case by completing troubleshooting of the issues and analysis on major or repeat issues and contributing knowledge articles, playbooks, or reusable troubleshooting guidance that reduce repeat volume. Contribute to High priority support or production-support responsiveness where applicable by providing fast technical guidance, validating escalation paths, and helping the broader support organization make better decisions earlier in the case lifecycle. Act as a technical role model for quality, ownership, and judgment in how cases are investigated, escalated, documented, and resolved. Contribute to responsible AI adoption by using sound judgment, validating outputs, and ensuring that final recommendations, communications, and actions remain accurate and customer ready. Help embed AI into support ways of working by sharing effective use cases, improving repeatable practices, and supporting continuous improvement across the team. 12-Month Success Signals Consistently meets or exceeds SLA targets and maintains high CSAT scores. Reduces complex escalation backlog and improves average resolution time. Contributes documented root-cause fixes that decrease repeat incidents. Delivers measurable efficiency gains through AI-assisted workflows (e.g., reduced case handling time, improved documentation speed). What You'll Need to be Successful At Avalara, this role is expected to be a bar raiser for Support Engineering, leveraging technical expertise, data-driven insights, and AI-enabled capabilities to elevate troubleshooting, accelerate issue resolution, and prevent recurring customer problems. They continuously improve support operations, knowledge management, and team effectiveness while delivering exceptional customer outcomes. Raise the bar for the team. Provide guidance, improve execution quality, and leave cases, routing, and knowledge resources better than you found them. Own complex cases end to end. Drive the issue forward, clarify ambiguity, follow up proactively, and make sure cases do not stall waiting on others. Identify and drove resolution of recurring product defects, resulting in improved customer experience and reduced support volume. Consistently achieve high customer satisfaction scores through effective issue ownership, technical expertise, and proactive communication. Reduce critical issue resolution time to 5 days through structured root cause analysis and cross-functional collaboration. AI Bar Raiser Expectations: This role is expected to be an AI Bar Raiser, applying AI in a deliberate and impactful way to improve how technical issues are diagnosed, resolved, and prevented, while elevating the team’s ability to use AI to drive meaningful gains in support efficiency, knowledge quality, technical troubleshooting, and customer outcomes. Leverage AI-powered tools to accelerate root cause analysis and reduce troubleshooting time for complex customer issues. Identify and implement new AI-driven approaches to technical support (e.g., automated diagnostics, intelligent case triage, predictive risk identification) that go beyond current team practices Utilize Generative AI to create knowledge base articles, troubleshooting guides, and customer-facing documentation, improving knowledge accessibility and consistency Develop AI-driven workflows that automated repetitive support tasks, increasing team productivity and reducing manual effort. Create AI-powered prompt libraries and support playbooks that standardized troubleshooting approaches across the team. Collaborate with Product and Engineering teams to integrate AI-driven customer feedback analysis into product improvement initiatives. Champion AI adoption across the support organization, driving measurable improvements in resolution efficiency and support quality. Use AI insights to prioritize critical customer issues based on business impact, severity, and historical trends.