AI Support Engineer

About We Suite

A Fluent Software Group Company

WeSuite builds specialized software for the security systems industry — helping integrators and dealers manage quoting, sales workflows, and client relationships more effectively. We're on a mission to build a support organization where AI agents handle the majority of resolution work, freeing our team to focus on what requires genuine judgment, product expertise, and client relationships.

We take AI seriously as infrastructure, not just tooling — and we're looking for people who do too.

This is not a traditional support role with AI tools added on. It's an agent-building and agent-ownership role that requires genuine support instincts, strong technical curiosity, and a systems mindset. You'll resolve real tickets, develop deep product knowledge, and constantly think about how to turn what you just learned into something an agent can handle next time — without human intervention.

Agent Development & Ownership

• Own the performance of WeSuite Walt, our support bot, as a product responsibility — not a side task
• Design, build, and iterate on agent resolution flows for defined ticket categories
• Identify ticket classes suitable for full or partial autonomous resolution and drive them to automation
• Prompt engineer and tune agent responses against real ticket data, measuring accuracy and resolution rate
• Establish and close feedback loops: when an agent fails, diagnose why, fix the underlying gap, and retest
• Continuously expand the scope of what agents can resolve without human intervention

Product Knowledge as Infrastructure

• Work a meaningful volume of real tickets as a core part of the role — this is how client understanding and product knowledge are built and kept current
• Treat every ticket as a data point: does the agent know how to handle this? If not, why not, and what needs to change?
• Develop expert-level fluency in WeSuite's platform, common failure modes, and client use patterns to translate that knowledge into agent-ready content and logic
• Collaborate with QA and Product Management to stay ahead of platform changes that affect agent accuracy

Knowledge Infrastructure

• Own and manage the Knowledge Base as a living system agents draw from — not a static document library
• Use AI tools (Gemini, Scribe, etc.) to accelerate article creation while owning the quality and structure of what gets published
• Ensure Knowledge Base architecture supports agent retrieval — structure, tagging, and coverage matter as much as content quality

Escalation & Defect Triage

• Handle escalations that agents cannot resolve, using Devin AI to structure and analyze code defects before Development handoff
• Collaborate with QA to validate resolution before new releases
• Actively work to reduce the escalation rate over time by feeding learnings back into agent workflows

Metrics & Continuous Improvement

• Track and own agent performance metrics as the primary measure of role success
• Report on automation coverage, deflection rate trends, and resolution quality alongside traditional support KPIs
• Bring a continuous improvement mindset to both the agent layer and your own direct support work

Qualifications

• 3–5 years of SaaS customer support experience, preferably in an enterprise environment
• Demonstrated experience building or improving AI agents, chatbots, or automated support workflows — not just using AI tools passively
• Strong prompt engineering instincts and comfort working iteratively with LLM-based tools
• Hands‑on Zendesk experience including workflow configuration and reporting
• Ability to develop deep product knowledge quickly and translate it into structured, agent‑usable content
• Strong written communication skills — clarity of thought directly impacts agent quality
• Comfort operating in a metrics‑driven environment with ownership over outcomes, not just activities

Nice‑to‑Haves

• Experience owning a support bot or virtual agent end‑to‑end
• Familiarity with knowledge base architecture and content strategy for agent retrieval
• Exposure to structured defect reporting or basic QA processes
• Background in sales, quoting, or CRM‑adjacent SaaS platforms
• Experience with…