# AI Engineer at Suitsupply

> Netherlands · Unspecified · ML / AI · open. Source: https://alderhq.app/jobs/greenhouse%3Asuitsupply%3A8184765 (read 2026-11-08).

## Facts (observed)

- Company: [Suitsupply](https://alderhq.app/companies/suitsupply)
- Location text: Amsterdam, Noord-Holland, The Netherlands; HQ Amsterdam
- Where it can be done from (inferred): Netherlands (evidence: "Location: Amsterdam, Noord-Holland, The Netherlands; HQ Amsterdam")
- Posted: 2026-09-07 (63 days ago)
- First seen by alder: 2026-11-07 · last verified: 2026-11-07
- Reposted: 0 times · edited: 0 times
- Apply on the employer's site: https://careersatsuitsupply.com/en-us/vacancies/8184765?gh_jid=8184765
- Skills listed (inferred): Python, GCP, LLMs

## Pay and sponsorship

- Posted pay: not posted
- Market band for similar posted roles (Amsterdam, n 3): p25 €77k, median €86k, p75 €104k

## Description (the employer's text)

### As one of Suitsupply’s first dedicated AI Engineers, you will build the agents that turn our GCP data platform and governed context layer into automated, tool-calling workflows running real business processes. This role is forward-deployed: you will embed with the teams doing the work, identify the highest-leverage processes to automate, and ship production-grade agents rather than prototypes. You will lay the reusable “golden path” — skills, connectors, evals, and templates — that make every agent built after yours faster to deliver. Joining early means helping shape the Data & AI team’s standards as it scales, with your impact measured in agents shipped and hours returned to the business. You will report into the Director of Data.

### What You Will Do

- Embed with the teams doing the work, map how a process actually runs, and identify the single highest-leverage opportunity to automate.
- Build tool-calling agents on our platform that take real processes off people’s plates as reliable production systems, not prototypes.
- Turn every build into reusable skills, connectors, evals, and templates, so agent-building gets faster each time.
- Hand off cleanly, leaving a running system with a runbook, an eval framework, and a named owner.
- Define what “good” looks like for agents — accuracy, cost, guardrails, sensitive-data handling — and mentor the per-team champions who scale it.
### Who You Are

- A production software engineer first, with strong Python and real fundamentals in testing, APIs, version control, and observability.
- Proven experience building agentic workflows, RAG, and tool-calling systems that run in production, not just in demos.
- Evaluation-driven: you set a baseline, define the metrics that matter, and prove with numbers that a change moved the needle.
- Fluent in GCP and Vertex AI, comfortable in the Claude ecosystem (Claude Code, MCP, skills), and at home in BigQuery.
- Forward-deployed by temperament, thriving in ambiguity and able to translate business problems into technical plans for a director and an engineer alike.
- Approximately 5+ years in software engineering with production AI experience, strong product sense, and the judgment to know when to prototype, harden, or stop.
### What You Will Get

- Autonomy: We empower you to take ownership, make meaningful decisions, and drive impact without layers of sign-off.
- Growth: We see your potential as a key asset. At Suitsupply, you’ll have abundant opportunities to learn, grow, and excel in a supportive environment that encourages development at every step.
- Corporate Social Responsibility: Our commitment to sustainability and ethical business is unwavering. We work exclusively with suppliers who uphold the highest standards, in alignment with the International Labour Organization.
- Style: Immerse yourself in a world of beautifully crafted, high-quality products, and enjoy a 40% discount on Suitsupply products.
- Compensation: We offer a competitive salary of based on relevant skills and experience.

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Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/greenhouse%3Asuitsupply%3A8184765 and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.