Asks for

The ad says“Working SQL and BigQuery: you read and write SQL comfortably and can connect an application to BigQuery to read, write, and update data”
The ad says“Hands-on Google Cloud experience with services such as Cloud Run (or GKE), Pub/Sub, Cloud Scheduler/Workflows, Cloud Logging & Monitoring”
The ad says“Hands-on Google Cloud experience with services such as Cloud Run (or GKE), Pub/Sub, Cloud Scheduler/Workflows, Cloud Logging & Monitoring”
The ad says“Hands-on Google Cloud experience with services such as Cloud Run (or GKE), Pub/Sub, Cloud Scheduler/Workflows, Cloud Logging & Monitoring”
The ad says“Hands-on Google Cloud experience with services such as Cloud Run (or GKE), Pub/Sub, Cloud Scheduler/Workflows, Cloud Logging & Monitoring”
The ad says“Hands-on Google Cloud experience with services such as Cloud Run (or GKE), Pub/Sub, Cloud Scheduler/Workflows, Cloud Logging & Monitoring”
The ad says“Hands-on Google Cloud experience with services such as Cloud Run (or GKE), Pub/Sub, Cloud Scheduler/Workflows, Cloud Logging & Monitoring”
The ad says“Hands-on Google Cloud experience with services such as Cloud Run (or GKE), Pub/Sub, Cloud Scheduler/Workflows, Cloud Logging & Monitoring”
The ad says“Applied LLM experience in production: agents or LLM-backed services you shipped and operated, including evaluation, guardrails, cost, and latency management”
The ad says“Hands-on Google Cloud experience with services such as Cloud Run (or GKE), Pub/Sub, Cloud Scheduler/Workflows, Cloud Logging & Monitoring”
The ad says“REST API and webhook experience: you've integrated multiple third-party systems from scratch”
The ad says“Working SQL and BigQuery: you read and write SQL comfortably and can connect an application to BigQuery to read, write, and update data”
The ad says“REST API and webhook experience: you've integrated multiple third-party systems from scratch”

We're looking for an Agentic AI Engineer to join our team in Helsinki or Dublin. You'll own the platform layer that makes our entire GTM AI agent programme work: shared infrastructure, event routing, data connections, deployment pipeline, and observability that every agent depends on. This is a software engineering role, not a workflow-automation role, you'll be writing and shipping production services on Google Cloud.

This role is for you if:

You have a strong interest in agentic AI and where it changes what automation can do
You think in systems and design for maintainability
You've owned the pager for something that mattered
You can sit with a non-technical GTM stakeholder, understand the actual problem, and translate it into an infrastructure decision
You're comfortable in a fast-moving environment where the patterns are still being set, and comfortable being the one who sets them

Must have:

Experience building and running production software: services you personally deployed, monitored, and were on the hook for when they broke
REST API and webhook experience: you've integrated multiple third-party systems from scratch
Applied LLM experience in production: agents or LLM-backed services you shipped and operated, including evaluation, guardrails, cost, and latency management
Hands-on Google Cloud experience with services such as Cloud Run (or GKE), Pub/Sub, Cloud Scheduler/Workflows, Cloud Logging & Monitoring
Working SQL and BigQuery: you read and write SQL comfortably and can connect an application to BigQuery to read, write, and update data

Nice to have:

Google-native AI tooling (Vertex AI, Agent Builder, Gemini API)
Direct experience with Salesforce, HubSpot, Gainsight, or Zendesk APIs
Experience in a RevOps, SalesOps, or MarketingOps-adjacent environment

Responsibilities:

Build and maintain the shared infrastructure for all AI agents run across the GTM org, including business development, sales, customer success, and support
Ensure all agents connect to tools like Salesforce, Gainsight, and Zendesk in a consistent way
Own and maintain the GTM Agent Registry: the master catalogue of every agent, what it does, who owns it, and when it was last reviewed
Set up and maintain observability, dashboards, and logs so the team can see what agents are doing and catch issues quickly
Maintain data quality and act as write authority on the Golden Record (BigQuery)

Benefits we offer…

Attractive salary and benefits package, including equity participation
Great work equipment, and home office allowance for fully remote locations
Health care benefit and leisure time insurance
Annual personal learning budget
Sports and wellbeing allowance

Benefits may vary depending on location.

#LI-Hybrid

Join us in putting AI to work for marketers

Supermetrics helps marketers make better decisions. It connects marketing data from platforms like Facebook Ads and Google Analytics to the AI tools, analytics tools, and data warehouses marketers already use, putting it right where they need it.

With Supermetrics, a marketer can connect their data to AI tools like Claude and ChatGPT, ask questions about their campaigns, and get insights and recommendations grounded in live data. From there, they can also manage and update campaigns across every connected platform, automatically and in one place, using guardrails to stay in control.

We work with organizations of every size: small teams that want enterprise-level reporting without the overhead, global brands like Dyson and L'Oréal that need visibility across millions in ad spend, and agencies like dentsu and McCann UK that manage large portfolios of client accounts at scale. In total, over 200,000 businesses trust Supermetrics to help them make the best decisions with their marketing data. We've grown from a one-person shop in 2013 into a global powerhouse, and we're only getting started.

Today, we're 300+ people, with teams spread across 10 countries and 3 continents. Our team represents more than 50 nationalities which makes us a multicultural, collaborative, thriving team.

Supermetrics operates on trust, transparency, and a keen customer focus. Forward-looking and quick to act, we see what needs doing, take ownership, and run with it. As team players, we help each other and win together.

We're hiring for a diverse, skilled, and collaborative team and building an inclusive workplace where everyone is treated fairly and respectfully.

It all started with a Google t-shirt... Read the rest of our story at supermetrics.com/about.

How we use AI in the recruitment process:

We use AI to help our recruiters work through applications faster, for example, summarizing your resume and scheduling interviews. A recruiter reviews every application, and no hiring decision is ever made by AI.

For some roles, your first interview may be with an AI interviewer instead of a person, and a recruiter reviews that conversation before deciding whether you move forward. From there, our human interviewers may use AI to take notes throughout the rest of the process, never to score or evaluate you, just so they can stay focused on the conversation instead of typing. You'll be told before this happens, and if you'd rather not be recorded, you can opt out at any point. It covers the rest of your process and never affects how you're evaluated. Every hiring decision is made by our human recruiting and hiring teams.

Asks for

Values