AI Data Engineer

We are building an AI Transformation program that automates real work across the company - support, onboarding, finance, sales operations - with measurable results. As our first AI Data Engineer you build the foundations that make that possible: the data pipelines, integrations, and agentic workflows that turn AI from demos into production systems, plus the measurement layer that proves what they deliver. You report directly to the Director of AI Transformation and work with every department in the company.

What you will do

• Build AI automation (core, ~70%). Design, build, and run agentic workflows and process automations end-to-end: extract and prepare data from source systems (CRM, ticketing, finance, product), orchestrate Azure AI Foundry models in agentic frameworks (durable Azure Functions) with tool-calling and retrieval, write results back into systems of record, and wrap everything in evaluation, monitoring, and guardrails so it keeps working after launch.

• Own the data plumbing. Build and maintain the pipelines and integrations the AI portfolio depends on - and the baseline/impact measurement data (hours saved, quality metrics) the program reports to the board.

• Support the analytics estate (~30%). Maintain and extend our Power BI reporting: semantic models, report building, and helping business users answer their own questions. This share is deliberately bounded - the core of the role is building, not servicing tickets.

• Shape what gets built. Join discovery workshops with departments, assess technical feasibility of automation candidates, and influence the decision per case: build custom, configure Copilot Studio, lean on SaaS-embedded AI, or skip

• 4+ years building data pipelines and integrations in production - Python and/or C#, SQL, REST APIs; our stack is Azure Data Factory, Azure Functions, Blob Storage, and DuckDB

• Hands-on experience building agentic solutions with LLM APIs (Azure AI Foundry, OpenAI, Anthropic or similar) - RAG, structured output, tool-calling, agentic frameworks - and testing/evaluating what they produce

• An AI-native way of working: agentic coding tools (Claude Code, Cursor, Antigravity, GitHub Copilot or similar) are part of your daily workflow, and you can articulate where they accelerate you and where they mislead

• Working proficiency in Power BI: data modeling, DAX, report design

• Software engineering discipline: version control, code review, CI/CD, monitoring - you build systems that run unattended

• Strong communication with non-technical colleagues; comfortable turning a messy process description into a technical design

• Pragmatism: you ship a working 80% solution and iterate, and you flag when automation is the wrong answer

Nice to have

• Experience in B2B SaaS operations (support, onboarding, CS tooling ecosystems)

• Copilot Studio / Power Platform, or experience extending SaaS-embedded AI features

• Familiarity with privacy-aware data handling (GDPR)

• Dutch language skills (if NL-based)

What success looks like

• 6 months: 2-3 process automations live in production with baselines and measured savings; BI support running through a structured intake with satisfied stakeholders; measurement dashboard feeding the monthly program report.

• 12 months: A reusable automation platform (shared pipeline patterns, evaluation harness, monitoring) so each new initiative ships faster than the last; contributing technical design to at least one larger process-reengineering initiative.

At Experlogix, we strive to create a culture of dedicated and engaged team members with a strong organizational commitment. We emphasize growth and place people in careers, not jobs, with opportunities to grow personally and professionally. Our purpose is to fuel your passion through rewarding careers and opportunities! See why we were named a Top 10 Dynamics Marketplace solution by Microsoft and as one of the best software and service companies in the Silicon Slopes!