Customer Support
Serving and retaining customers after the sale. Covers customer success, customer support/technical support, customer experience, implementation/onboarding, customer operations, renewals (retention-focused), professional services, and customer education/training.
Roles
The canonical roles within Customer Support.
Customer Success Manager
Customer Success Managers at AI companies own a portfolio of post-sale customer relationships, with accountability for adoption, retention, and expansion across the contract lifecycle. The day-to-day is classical CSM: running structured onboarding, monitoring customer health, driving usage against agreed success criteria, navigating renewals, and identifying expansion opportunities through ongoing partnership with the customer's stakeholders. CSMs at AI companies need working fluency in their company's product so they can guide customers through implementation, but the deeper technical work—integration architecture, deployment design—usually sits with solutions engineering or forward-deployed counterparts. These roles typically sit within dedicated customer success teams, partnering with sales on renewals and expansion, with product on customer feedback, and with support on escalation paths.
Technical Support Engineer
Technical Support Engineers at AI companies own the diagnosis and resolution of customer-reported technical issues—working tickets across API and SDK integration, authentication and access, deployment and configuration, and product behavior. The day-to-day is classical technical support engineering: reproducing issues, analyzing logs and telemetry, performing root-cause analysis across multi-component systems, communicating clearly with customers across technical levels, and partnering with engineering on durable fixes for systemic issues. The specific surfaces vary by product—API support at platform companies, deployment and integration support at infrastructure companies, product support at application companies—and AI-specific failure modes (model behavior, inference performance, agent debugging) appear in some of these jobs, but the foundational role is recognizable across any developer- or enterprise-software company. These engineers typically sit within customer support, customer experience, or developer experience teams, partnering with engineering on escalations and product feedback.
Engagement Manager
This role oversees the full lifecycle of technical implementations and ongoing customer partnerships for enterprise AI platforms, managing multiple concurrent engagements while serving as the primary point of contact for strategic accounts. Engagement Managers distinguish themselves through their ability to balance project management rigor with trusted advisor relationships, embedding themselves within customer teams to drive adoption of AI capabilities—whether for data platforms, revenue intelligence systems, or enterprise search solutions. They typically sit within Professional Services organizations alongside Solution Architects and AI Engineers, operating at the intersection of delivery execution, customer success, and account growth.
Support Operations Specialist
Support Operations Specialists at AI companies own the systems, workflows, and team-level performance that keep customer support functioning as the company scales. In practice at AI companies this canonical role frequently extends into support team leadership and management—coaching agents, running performance reviews, owning headcount and capacity—alongside the operations work of designing workflows, configuring tooling, maintaining the knowledge base, and reporting on KPIs. The boundary with a Support Manager title is fuzzy across the population, with many jobs in this slug carrying both responsibilities. These roles typically sit within customer support or customer experience organizations, partnering with product and engineering on tooling and product feedback, and with people operations on team-related questions.
Implementation & Deployment Specialist
Implementation & Deployment Specialists guide enterprise customers through complex technical integrations and go-live processes for AI-powered platforms and systems. They work hands-on to configure environments, troubleshoot deployment challenges, and translate customer business needs into technical solutions—often serving as the primary technical bridge between customer teams and internal engineering. What distinguishes this role is its dual focus: balancing deep technical acumen with strategic customer relationship skills, ensuring both flawless execution and long-term adoption across diverse infrastructure environments. These specialists typically embed themselves in customer organizations during critical implementation phases, then gradually transition customers toward self-sufficiency while capturing insights that inform product development.
Account Manager
Account Managers serve as the primary commercial and strategic advisor to existing customers, owning the full post-sale lifecycle from adoption through renewal and expansion. These roles focus on protecting and growing customer accounts by understanding evolving business needs, uncovering new use cases for AI products, and navigating complex renewal negotiations with multiple stakeholders. Account Managers typically sit within dedicated account management teams alongside customer success and sales counterparts, acting as the quarterback between customers and internal product, engineering, and operations teams to ensure long-term partnerships deliver measurable business outcomes.
Customer Enablement & Education Specialist
This role designs and delivers scalable training programs that accelerate customer adoption of AI products, translating technical capabilities into measurable business outcomes. Specialists work across the full customer lifecycle—from initial onboarding through advanced use cases—partnering with sales, product, and success teams to create structured enablement paths. What sets this apart from support is its focus on proactive skill-building and value realization rather than reactive problem-solving. These professionals typically embed within go-to-market or customer success functions at growing AI companies, serving as strategic advisors who blend technical fluency with instructional design to help enterprise customers maximize platform impact.
Recent Jobs
The latest Customer Support openings across the AI industry.