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Jesus Zenteno

AI Agent Operations  ·  Conversation Design  ·  Support Automation

(404) 406-6034jzentenoa@gmail.comForest Park, GAlinkedin.com/in/jesus-zenteno-4b5306124jesuszenteno.vercel.app

Professional Summary

Support Operations professional with 7+ years at The Weather Company specializing in AI agent design, workflow automation, and support systems integration. Hands-on experience configuring and optimizing AI support agents (Decagon), building agentic n8n workflows, and applying prompt engineering to drive measurable outcomes — including a 200%+ increase in QA review capacity. Skilled at designing conversation flows, human-in-the-loop handoffs, and integrating external APIs to enable AI agents to resolve issues end-to-end.

Core Competencies

AI Agent Configuration & Optimization
Decagon AI · n8n · Claude Code
Conversation Design & Handoff Logic
Prompt Engineering & LLM Refinement
API Integrations & Workflow Automation
RAG System Architecture
KPI Analysis (CSAT, Automation Rate)
Cross-functional Stakeholder Management
Human-in-the-Loop Workflow Design

Professional Experience

Technical Lead, Customer Service AI

The Weather Company, an IBM Business  ·  Atlanta, GA

November 2025 – Present
  • Primary internal stakeholder for AI vendors; led the technical transformation of the Customer Service department.
  • Configured and optimized Decagon AI agent behaviors — guidance rules, triage logic, inbound categorization, and conversation flow design — improving response quality, tone consistency, and automation rates.
  • Designed Human-in-the-Loop handoff workflows in n8n, enabling seamless escalation between AI and human agents with context preservation and routing logic tailored to customer segment and issue type.
  • Built API integrations connecting the AI agent to external data sources (Sports APIs, celestial data, editorial templates), enabling the agent to take real action on behalf of users.
  • Applied advanced prompt engineering to refine LLM models for predictive case labeling and automated replies — significantly improving accuracy and reducing human review time.
  • Architected an internal RAG system to serve as a scalable AI knowledge base, ensuring consistent, context-aware responses and proving the business case for expanded AI investment.
  • Launched an automated QA agent that increased review capacity by 200%+, eliminating manual workload equivalent to one FTE — measured through automation rate and resolution KPIs.
  • Leveraged Claude Code to accelerate development of custom JavaScript nodes for n8n, building logic that standard support tools could not handle.

Customer Support Delivery Team Leader

The Weather Company, an IBM Business  ·  Atlanta, GA  (Concurrent with Technical Lead role)

August 2020 – Present
  • Managed daily operations for a global team of 11 support representatives, monitoring SLAs and KPIs to ensure AI capability rollouts did not disrupt service quality.
  • Tracked CSAT, resolution time, and escalation patterns to identify improvement opportunities and inform AI optimization priorities.
  • Acted as the bridge between non-technical support agents and engineering teams, translating complex user pain points into technical requirements for internal tooling and AI agent configuration.
  • Served as Voice of the Customer for Product and Engineering — transforming unstructured user feedback into actionable intelligence that directly influenced the product roadmap.

Customer Support Specialist

The Weather Company, an IBM Business  ·  Atlanta, GA

March 2019 – August 2020
  • Authored complete functional specifications for a new Customer Support tool, working in Agile sprints alongside developers through successful launch.
  • Analyzed user-reported issues to improve documentation and FAQ precision — building knowledge management skills foundational to tuning AI knowledge bases.

Associate System Engineer, TOC Agent

The Weather Company, an IBM Business  ·  Atlanta, GA

February 2016 – March 2019
  • Monitored 600+ internal and external production systems using Zabbix and Catchpoint.
  • Built foundational knowledge of system reliability, SaaS infrastructure, and exception handling critical to safe AI agent execution.

Education & Certifications

Year Up Atlanta

Technical and professional training program

Generative AI: Introduction and Applications

IBM