Principal Agentic Architect - 11386

What You'll Do:

AI Engineering & Agentic Orchestration

Own the build, configuration, and rapid prototyping of AI agents within Coupa Agent Studio, extending platform capabilities beyond standard out-of-the-box functionality

Specialize in prompt engineering, model tuning, and AI guardrails to ensure accuracy, reliability, and reduction of hallucinations within production AI workflows

Leverage multiple AI platforms, frameworks, and orchestration tools including Claude, OpenAI, MCP, and LangChain to design best-of-breed agentic workflows

Design and deploy extensibility frameworks including Embedded UI Assistant integrations and Model Context Protocol (MCP) capabilities for secure enterprise orchestration

Develop agent-to-agent communication logic and workflow orchestration across complex multi-step business processes

Integration & Technical Leadership

Leverage deep API and integration expertise to support secure, low-latency connectivity between AI agents and enterprise systems including ERP, CLM, and CRM platforms

Partner directly with customer IT and security teams to address technical feasibility, risk assessments, governance, and enterprise security requirements

Understand and manage AI consumption strategies, platform resource utilization, and Coupa credit usage across agentic workflows

The Field-to-Product Bridge

Act as the primary technical liaison between customer engagements and Product Management, identifying roadmap gaps and influencing future platform capabilities

Ensure technical delivery remains aligned to original architectural vision and “as-designed” specifications throughout implementation lifecycle

Support technical pre-sales initiatives by developing reusable Agent Blueprints and rapid deployment PoCs while serving as a technical feasibility expert

Performance Tuning & Quality Assurance

Design authorization boundaries, simulation runs, and human-in-the-loop controls that govern autonomous AI decision-making and escalation paths

Develop evaluation frameworks and automated testing approaches focused on functional correctness and production-grade AI performance

Own ongoing monitoring, testing, health checks, and remediation of AI agents and workflow orchestration environments

Apply continuous improvement methodologies and human-in-the-loop best practices across AI-enabled technical solutions

What You Will Bring to Coupa:

Must-Have Technical Expertise

Proven experience in technical integration roles including Middleware, API Engineering, or Systems Architecture with strong knowledge of REST, GraphQL, and JSON

Strong programming proficiency in Python and/or JavaScript (Node.js)

Experience building integrations and orchestration layers between non-deterministic AI systems and deterministic enterprise platforms

Understanding of Source-to-Pay (S2P) business requirements with the ability to map agentic workflows across procurement, invoicing, and payables processes

Hands-on experience with agentic frameworks and open-standard orchestration architectures including MCP, LangChain, AutoGen, or similar technologies

Desired “Super Powers”

Strong builder mindset with the ability to rapidly move from concept to functional, deployable AI components

Advanced troubleshooting and debugging skills across complex AI systems, APIs, prompts, integrations, latency, and data quality issues

Ability to establish technical credibility and trust with executive stakeholders while acting as a strategic advisor on AI transformation initiatives

Experience supporting enterprise digital transformation and strategic consulting engagements within large-scale environments

Strong technical agility with the ability to quickly redesign and optimize agent logic within fast-paced implementation environments

Ability to clearly explain technical behaviors, limitations, and AI outcomes to non-technical stakeholders while building customer confidence

Deep understanding of Coupa APIs, Compose, configurations, and platform architecture with the ability to diagnose whether issues stem from AI logic, product limitations, data quality, or configuration setup

Proactive approach to customer education and expectation-setting throughout implementation and deployment processes