Partner with Sales and Customer Success to deeply understand customer requirements, translate them into technical solutions, and serve as a trusted advisor from initial evaluation through deployment and expansion
Lead technical discovery to map customer workflows, identify automation opportunities, and design agent architectures that deliver measurable value
Build and optimize AI agents—configuring workflows, writing and refining prompts, and tuning agent behavior to meet customer requirements
Own integrations between Zip AI agents and customer systems (ERPs, CLMs, ticketing, TPRM, and other procurement tools) using middleware and iPaaS platforms
Drive successful implementations end-to-end—scoping requirements, documenting architecture, testing configurations, troubleshooting issues, and ensuring smooth go-lives
Enable customer teams to manage and improve their agents, building confidence and long-term self-sufficiency
Gather insights on how customers are deploying AI agents, identify emerging patterns, and deliver structured feedback to Product and Engineering

Requirements

5+ years of experience in technical customer-facing roles such as Solutions Architect, Solutions Engineer, Technical Consultant, or Implementation Engineer
Hands-on experience building or deploying AI/LLM-powered solutions, with a working understanding of functional LLM fundamentals and prompt engineering
Strong technical credibility—you can lead architectural discussions, work through complex integration challenges, and earn the trust of technical stakeholders
Experience with middleware platforms, iPaaS tools, or integration architecture; comfortable with REST APIs, webhooks, and authentication protocols
Track record of managing enterprise customer engagements and delivering successful implementations in fast-paced environments
Strong communication skills with the ability to translate technical concepts for non-technical stakeholders across procurement, finance, and operations
Extreme attention to detail and a relentless focus on customer outcomes.
Nice to Have: Experience with agent-building tools (e.g., n8n, Glean) or familiarity with MCP (Model Context Protocol)
Background in ERP, P2P, CLM, or procurement systems
Python or JavaScript scripting experience

Benefits

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Applicant Tracking System Keywords

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Hard Skills & Tools

AI solutionsLLM fundamentalsprompt engineeringintegration architectureREST APIswebhooksauthentication protocolsPythonJavaScriptagent-building tools

Soft Skills

communication skillsattention to detailcustomer outcomes focustechnical credibilitytrust buildingproblem-solvingcustomer engagement managementarchitectural discussion leadershipworkflow mappingautomation opportunity identification