Description
Organizations want to deploy Gen-AI safely, efficiently, and measurably. You'll help them achieve this: from selecting the right tools and integrations to adoption, governance, and working agreements. You'll work closely with operations—you won't just "deploy" AI, you'll ensure teams can use it every day .
What are you going to do?
Implementing AI solutions : Rolling out and configuring solutions such as Microsoft 365 Copilot, Google Workspace Gemini, and Slack AI, including roles/permissions, policies, and guardrails.
Operationalize use cases : select top tasks with departments, design workflows and templates (prompts, checklists, playbooks) and embed them in processes.
Integrations & Automation : Connections with existing SaaS and business applications (Power Automate/Zapier/Make or lightweight code-first scripts).
Adoption & enablement : building a champions network, organizing short hands-on sessions/office hours, and removing barriers.
Train/educate teams in effective and safe Gen-AI use within their own work systems (e.g. M365, Workspace, Slack, ERP/CRM), with concrete templates and best practices.
Measure & Improve : Monitor usage, quality, costs, and risks; translate insights into iterations on policy, prompts, templates, and working methods.
Stakeholder management : aligning with IT/security/legal and management teams; ensuring clear decision-making and progress.
Who are you?
Completed university master's degree (e.g. Artificial Intelligence, Data Science, Computer Science/IT or similar).
1–3 years of experience in consulting, operations, data/AI, or productivity tools.
Current knowledge of the LLM landscape (closed vs. open-source, context, tool/function use, RAG vs. fine-tuning, cost/latency trade-offs).
Experience in implementing AI productivity tools (Copilot/Gemini/Slack AI) and a sense of security, privacy and compliance.
Familiar with no/low-code automation; basic knowledge of Python/TypeScript is a plus.
Strong communication: you can clearly explain choices, risks and ROI to teams and management.
What do we offer?
Which AI tooling suits our stack and why ?
How do we ensure safety and governance without hindering innovation?
When do you choose RAG over fine-tuning , and what does that mean for quality/costs?
How do we measure adoption and ROI and adjust accordingly?
Nice-to-have: Experience with change programs, didactic design, or internal academies/LMS; observability/telemetry for AI applications.
What do we offer?
Salary: €3,000–€4,000 gross per month (based on full-time), depending on experience
Working with a team of true AI professionals with academic and business backgrounds.
Hybrid working in Amsterdam and at clients' locations; impacting organizations that want to move forward.
Training budget & access to the latest tools.
Favorable bonus structure