Head of Technical Support

ResolveAI • San Francisco, CA

5d • Remote

About The Position

Resolve AI is seeking its first Head of Technical Support to build and lead a 24x7, global, AI-first support function. This role is crucial for ensuring customer success by providing reliable and efficient support for critical production systems. The Head of Technical Support will design the support model, establish service commitments, select and implement tooling, handle cases directly, and recruit and manage the support team as the company scales. This position is a key part of the Customer Engineering team, working alongside Solutions Engineering and Deployment Engineering to prevent support issues from overwhelming other engineering functions. The ideal candidate is a hands-on technical support leader with experience supporting developer or infrastructure products, a deep understanding of production incidents, and enthusiasm for leveraging AI technology in support operations.

Requirements

• 8+ years in technical support, support engineering, or SRE/production engineering roles.
• 3+ years leading a support function or team for a developer, infrastructure, observability, or B2B SaaS product.
• Experience building a support function from an early stage, including defining SLAs, severity models, setting up tooling, and designing 24x7 or follow-the-sun coverage for enterprise customers.
• Strong hands-on technical depth in production infrastructure: cloud platforms (especially AWS), Kubernetes, networking and authentication (SSO/SAML), and observability tools (e.g., Datadog, Grafana, Prometheus, Splunk, OpenTelemetry).
• Ability to dig into logs and reproduce customer problems.
• Active power user of AI agents and coding tools (e.g., Claude Code, Codex, Cursor) with experience automating support or operations workflows.
• Comfortable with prompting, context engineering, and critically evaluating LLM output.
• Proven track record of handling high-severity customer incidents calmly and communicating clearly with both engineers and executives.
• Experience working closely with Engineering on defect triage and escalation.
• Experience working with Sales and post-sales teams on account health.
• Data-driven approach: defining support metrics, building reporting, and using data to drive decisions.
• Strong sense of ownership, high bar for customer experience, ability to raise risks early, and comfort with ambiguity in an early-stage company.

Nice To Haves

• Experience supporting AI/ML or LLM-based products.
• Experience with support for global enterprise customers, including contractual support terms and compliance requirements (e.g., SOC 2).
• Scripting experience in Python, TypeScript, or Go for support automation and tooling.
• Experience building self-service knowledge bases or developer documentation.

Responsibilities

• Design and launch the support operating model, defining 24x7 global coverage, severity levels, response and resolution targets, escalation paths, on-call rotations, and follow-the-sun handoffs, and translating these into service commitments for customer contracts.
• Build an AI-first support experience using Resolve and other AI agents for triage, diagnosis, and resolution, deflecting common issues through self-service and documentation, and designing seamless agent-to-human handoffs.
• Work cases directly, owning the end-to-end process including triage, diagnostics, troubleshooting across integrations, cloud environments, and Kubernetes, maintaining case records, and communicating with customers.
• Ensure every case has a clear owner, documented impact and investigation, coordinated customer updates, and a documented resolution, especially during high-severity incidents.
• Collaborate closely with Engineering to differentiate configuration/usage issues from product defects, raise well-evidenced tickets, and provide necessary evidence for fixes.
• Partner with the account team to bring in relevant context, share case trends, and identify potential adoption or renewal risks based on support patterns.
• Define, establish, and report on key support metrics such as response and resolution times, SLA attainment, AI resolution rate, backlog health, CSAT, and case drivers, and use this data to drive improvements in product, documentation, and onboarding.
• Develop the staffing and coverage model, identify areas where human intervention adds the most value, and hire, onboard, and lead support engineers globally as customer volume grows.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed