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# AI Systems Analyst

- **Company:** Travelperk
- **Location:** Spain
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Data Integrity, Fault Tolerance, Python (Programming Language), Salesforce.Com, Software Engineering, Systems Integration, Large Language Models, Multi-Agent Systems, Zapier, Data Layers, Data Objects, Webhooks, Software Version Control, Data Pipelines, Automation Anywhere, Api Management
- **Published:** July 12, 2026
- **Apply:** https://es.trabajo.org/oferta-5354-36f6753b45f2f89f0c82d107b0af7f26

## About the Role

schemas, maintain data quality, and build monitoring logic that catches issues before they reach Sales. - Integrate with Salesforce at depth, including custom objects, flows, and automation, to reflect agent outputs accurately in the CRM and downstream reporting. Sales & GTM Team Enablement - Partner with GTM leadership to identify where manual effort can be replaced by intelligent automation, from account research and signal triage to follow-up sequencing and CRM hygiene. - Translate business problems into scoped, shippable agent systems, and surface realistic timelines and trade-offs rather than over-promising what AI can reliably do today. - Build tooling and interfaces that give non-technical teams visibility into agent activity and confidence in the outputs they are acting on. - Rapidly diagnose and resolve failures in production to minimise disruption to selling time. Technical Standards & Team Leverage - Set and maintain engineering standards for how AI systems are built:
version control practices, documentation, testing patterns, and deployment hygiene. - Share frameworks, code, and learnings with the broader GTM Engineering team to drive consistency across the function. - Provide clear feedback to inform roadmap prioritisation, surfacing where automation is working, where it is brittle, and where human judgment still beats a model. What We're Looking For Must-Have - 5+ years in a technical role building production systems, e.g., GTM Engineering, Revenue Systems, or software engineering with strong GTM exposure in a B2B SaaS environment. - Hands-on experience building multi-step AI agents using Python and LLM APIs (Claude, OpenAI, or equivalent) in a production context. - Strong Python engineering fundamentals: clean, maintainable, testable code and care about reliability vs. prototype. - Direct experience integrating APIs, webhooks, and event-driven flows using automation tooling (Make, n8n, Zapier, or equivalent) alongside
custom Python solutions. - Salesforce proficiency at the configuration layer: custom objects, flows, reporting, and data integrity logic. - Track record of translating ambiguous business problems into scoped, delivered technical solutions; ability to size problems and push back on unrealistic scope. - Strong instincts for system design: observable, recoverable, and without creating maintenance debt. Strong Advantage - Experience designing agent frameworks or shared infrastructure patterns that others build on. - Familiarity with GTM tooling landscape (Clay, O

## Description

revenue stack. - Architect agent systems that are robust in production with clear error handling, observability, and graceful degradation when upstream data or APIs misbehave. - Build the reusable agent framework, including shared abstractions, tooling patterns, and integration modules, so the wider Revenue Systems and GTM Engineering team can ship AI workflows without starting from scratch. - Evaluate and integrate emerging agentic tooling and patterns, recommending when to build vs. buy and which abstractions are worth investing in. Data Pipelines & Systems Integration - Build and maintain data pipelines that connect Salesforce, outbound tools, enrichment providers, and internal systems, ensuring clean, timely data for agents. - Engineer API integrations, webhook-driven triggers, and event-based flows using Python, Make, and equivalent automation tooling without requiring engineering support for each new connection. - Own the data layer that underpins AI decision-making: design


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