Designated Technical Support Engineer, Ops

Glean•Mountain View, CA

1d•Hybrid

About The Position

Glean is seeking a highly analytical individual to sit within the Support Organization and focus on making our Support team more effective through metrics, AI‑powered tooling, and operational excellence. This role involves defining and tracking support metrics, building dashboards, presenting insights, owning AI-powered support tools, analyzing their performance, and partnering with Product, Engineering, and Data Science to launch new AI use cases. The role also includes leading special projects to improve Support productivity and customer experience, designing and running A/B tests, analyzing workflows for inefficiencies, documenting processes, and defining SLIs/SLOs for Support operations and AI tools.

Requirements

5+ years of experience in CX Operations, Revenue Operations, or related GTM operations roles, ideally in B2B SaaS.
Track record of building or materially improving CS systems and processes (health scoring, renewals forecasting, playbooks, segmentation) and demonstrating measurable impact on retention, expansion, or health.
Strong understanding of key post-sales metrics and leading indicators
Experience operating in high‑growth or startup environments where you’ve had to build structure in ambiguity.
Curious: Eager to tackle process, workflow, and AI‑related challenges to improve team outcomes.
Customer‑driven: Motivated by improving both internal support processes and the end customer’s experience.
Systems thinker: You enjoy mapping how tools, data, and processes fit together and simplifying complexity for others.
Data‑driven experimenter: You’re comfortable forming hypotheses, running experiments, and measuring impact, especially around AI and automation.
Continuous learner: Always looking for opportunities to document, measure, and refine team practices as AI capabilities evolve.

Nice To Haves

Proficiency with SQL and at least one BI platform (e.g., Sigma, Looker, Metabase, Tableau).
Prior experience designing or operating support automations and AI agents (e.g., Fin, Glean agents, Zendesk bots, workflow tools).
Experience driving change management in support organizations, including training, communications, and adoption measurement.
Working knowledge of SaaS products and/or cloud technologies.
Familiarity with knowledge base management and content creation.

Responsibilities

Define, track, and continuously refine Support metrics, including ticket volume, TTR, CSAT, deflection, automation rate, containment, backlog health, and agent effort.
Build and maintain dashboards and recurring reports in spreadsheets and BI tools (e.g., Sigma / Looker / Tableau) to give Support and CX leadership clear visibility into performance and trends.
Present insights and recommendations to Support and CX leadership on a regular cadence, highlighting risks, opportunities, and the impact of AI/automation initiatives.
Serve as the operational owner for AI‑powered support tools (e.g., Glean agents, internal copilots, routing/triage bots, macros with AI, deflection experiences), including configuration, monitoring, and continuous improvement.
Analyze agent and automation performance (resolution rate, handoff quality, mis‑routes, downvotes) and run structured experiments on prompts, workflows, and routing rules to improve outcomes.
Partner with Product, Engineering, and Data Science to scope and launch new AI use cases for Support (e.g., intelligent routing, duplicate detection, auto‑tagging, SLA risk prediction, backlog forecasting).
Ensure AI/automation features are rolled out with clear guardrails, runbooks, and monitoring, and that human support workflows integrate smoothly with AI experiences.
Lead special projects that materially improve Support productivity and customer experience (e.g., new queue designs, channel strategy updates, AI rollout pilots, process re‑designs).
Own work‑back plans, stakeholder alignment, risks, and communication for these initiatives, ensuring projects land on time and with clear success metrics.
Partner with CX Ops and cross‑functional stakeholders to design and run A/B tests and quasi‑experiments across macros, forms, flows, and AI experiences, quantifying impact on FRT, TTR, CSAT, deflection, and agent effort.
Analyze support workflows and ticket data to identify operational inefficiencies and recommend process improvements across tools, queues, and channels.
Document support processes, SOPs, and runbooks; maintain internal knowledge base and enablement content for Support tooling and AI features.
Partner with Support leadership to define SLIs/SLOs for Support operations and AI tools, with clear alerting and actionable runbooks when thresholds are breached.