AI Revenue Systems Analyst

Perk; Barcelona; Híbrido; EUR 70.000 - 110.000; Jornada completa

Descripción de la vacante

Perk is building AI infrastructure that changes how a revenue team operates. The AI Revenue Systems Analyst is a senior individual contributor and the technical authority on agentic AI within Revenue Systems.

This role focuses on production-grade, multi-step agent systems that replace real manual work and leverages Python-backed workflows and API integrations. The role reports to the Senior Manager, Revenue Systems, and collaborates with the GTM Engineering team and Sales leadership.

Formación

• Senior individual contributor and the technical authority on agentic AI within Revenue Systems.
• Experience building production-grade, multi-step agent systems that replace manual work.
• Strong engineering instincts alongside strong business judgment.

Responsabilidades

• Design, build, and maintain multi-step AI agents using Python and LLM APIs that automate research, qualification, routing, and decision-making across the revenue stack.
• Architect agent systems that are robust in production with error handling and observability.
• Build reusable agent framework and integration modules for the wider team to ship AI workflows.

Conocimientos

Python

LLM APIs

Agent design

Production-grade systems

Herramientas

Claude

OpenAI

Make

Descripción del empleo

About Us

Perk (formerly TravelPerk) is the intelligent platform for travel and spend management. Built to tackle the time-consuming, manual work that gets in the way of real work, our tools automate everything from travel bookings to expenses, invoice processing, and more. By eliminating this shadow work that wastes hours, erodes morale, and saps innovation, we're on a mission to power real work, with real impact.

We're trusted by more than 12,000 companies worldwide, including Bolt, GoCardless, and Fabletics, and we're tackling the 7 hours of lost productivity per employee each week, a $1.7 trillion problem https://www.perk.com/shadow-work-report.

Founded in 2015, Perk has grown into a global company of more than 1,800 people across 12 offices globally, with headquarters in London and Boston. We combine innovation, control, and simplicity to transform how businesses work and how people feel at work.

At Perk, we're driven by our values, like being an owner, delivering a 7-star experience, and working as one team. We value curiosity, purpose, and mindset, not just knowledge, to unlock the power in your potential. Our talent team brings together leading minds from the travel, fintech, and SaaS industries, representing over 70 countries. If you're excited about having a real impact and shaping how millions of people experience work, we'd love you on the team.

Visit www.perk.com http://www.perk.com to learn more.

ABOUT THE ROLE

At Perk, we’re building AI infrastructure that changes how a revenue team operates. Not a layer of tooling bolted on top of existing workflows, but a foundation that makes intelligent automation the default way work gets done. The Revenue Systems team sits at the centre of this, responsible for the systems, data, and agents that power how Sales and GTM operate.

The AI Revenue Systems Analyst is a senior individual contributor and the technical authority on agentic AI within Revenue Systems. This is a role for someone who has moved past experimenting with LLMs and is building production-grade, multi-step agent systems that replace real manual work. Where the GTM Engineering function owns Clay-based outbound and enrichment infrastructure, the AI Systems Specialist owns the agent layer: the Python-backed workflows, API integrations, and reusable frameworks that let the team ship AI automation faster and more reliably over time.

The 12-month goal is not a list of shipped workflows. It is a reusable agent framework that the broader Revenue Systems and GTM Engineering team builds on top of. That means strong engineering instincts alongside strong business judgment: knowing which problems are worth automating, how to build systems that do not break quietly, and how to make your work accessible to non-engineers who depend on it.

The role reports to the Senior Manager, Revenue Systems, and works closely with the GTM Engineering team and Sales leadership. It is a highly visible role with a direct line of sight to commercial outcomes.

AI is embedded in how we work across every function. The tools you will use day-to-day are AI-enabled so you can move faster and spend more time on the work that matters. For this role specifically, working with AI is not a part of the job—it is the job. We will expect you to have strong opinions on where LLMs are actually useful today versus where they are unreliable, how to build systems that behave predictably in production, and where human judgment still beats automation. We will ask about how you use AI and how you build with it in your interviews, not to test tool knowledge, but to understand how you think.

WHAT YOU'LL DO

AGENTIC WORKFLOW DESIGN & BUILD

• Design, build, and maintain multi-step AI agents using Python and LLM APIs (Claude, OpenAI) that automate research, qualification, routing, and decision-making across the 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, that allows the wider Revenue Systems and GTM Engineering team to ship AI workflows without starting from scratch each time.
• Evaluate and integrate emerging agentic tooling and patterns, bringing well-reasoned recommendations on 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 the clean, timely data that agents depend on is always available.
• 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: designing schemas, maintaining data quality, and …