AI Workflow Lead(Amsterdam, NLD)

This is a Full-Time Role (40 hours per week, 5DWW) with no option for part-time work. While this is a remote-first opportunity, the candidate filling this role must be a resident of the Netherlands or in the U.K. at the start of employment. Additionally, they must be within commuting distance of our office in Amsterdam or London.
Please visit our Careers page to review all opportunities and submit your application for the role(s) that best fit your location and work authorization. This job ad will close automatically at 9:00AM EST on October 23rd.
About the Team
The Data & AI team is responsible for building B Lab's data platform, delivering on business priorities, and bringing AI into how B Lab works. We approach AI deliberately, and with people and planet in view. B Lab is currently exploring how to use AI in a responsible way, aligned with our values and mission. The team reports directly to the CTDO. AI Enablement is one of three pillars within Data Analytics & AI, the demand side of the Data & AI team. It drives responsible, practical AI adoption across B Lab through three connected roles. The Senior Manager of Data Analytics & AI leads the branch and brings the knowledge of B Lab's systems and data infrastructure. The AI Workflow Lead works with teams to design and scale AI workflows. The AI Enablement & Learning Platform Lead builds the learning paths and skills that help people use them well.
About the Opportunity
The AI Workflow Lead is B Lab's AI workflow builder: an internal “consultant” who works closely with teams on the ground to understand how they work, find where AI can add the most value, and turn those opportunities into scalable, responsible AI workflows. Aside from internal processes, as you grow an understanding of our products, you will be working closely with our Product team to help identify opportunities in which AI can add meaningful value.
The role takes an organisation-level view. It runs the discovery and design behind cross-team workflows, coordinates delivery with the Data & AI team, Data engineering and the teams involved, and helps build the champion networks that carry adoption forward. It keeps a continuous picture of how AI is being used across B Lab, and where it falls short. Those insights feed the training built by the AI Enablement & Learning Platform Lead, and the role measures whether the workflows and programmes we run actually deliver.
It sits within Data & AI and reports to the Senior Manager of Data Analytics & AI. Together with the AI Enablement & Learning Platform Lead, it brings insights back to shape AI strategy collectively, which is then taken to the CTDO. It works across every function, with Product & Platform Engineering, and with governance and compliance stakeholders. The role works closely with the AI Enablement & Learning Platform Lead and will cover core AI-enablement responsibilities during that role's parental leave.
Core Responsibilities
Workflow Discovery & Design (40%)
Work closely with teams on the ground to understand their processes, pain points and goals, using interviews, process mapping and design thinking to find high-value AI opportunities.
Design and ship team and organisation-level AI workflows from idea to scaled solution, coordinating with the Data & AI team, Data engineering and the teams impacted.
Identify and scope meaningful AI opportunities in product-facing surfaces such as the B Impact platform, partnering with Product & Platform Engineering, and with the data/platform team where data or ML builds are needed.
Turn successful pilots into standard, supported workflows that other teams can adopt.
Use-Case Pipeline & Landscape Monitoring (20%)
Run a structured use-case pipeline (intake → evaluate → pilot → scale), so AI adoption is systematic rather than ad hoc.
Continuously monitor how AI is being used across the organisation, including what works, where limitations appear, and where risks emerge, and feed these insights into the training built by the AI Enablement & Learning Platform Lead.
Scan the AI landscape for new tools, capabilities and risks, and evaluate tools against clear criteria, including responsible-use, privacy and security considerations.
Impact Measurement (15%)
Measure the impact of the AI workflows and programmes we run, including time saved, quality and ROI, and report clearly on what is working and what isn't. (People's skills progression is tracked by the AI Enablement & Learning Platform Lead.)
Build simple dashboards and analyses that make adoption and impact visible to stakeholders.
Insight, Strategy & Adoption Support (15%)
Together with the AI Enablement & Learning Platform Lead, report insights to the Senior Manager of Data Analytics & AI, so that AI strategy is shaped collectively and based on operational reality.
Recommend where to invest in tools and workflows; decisions are co-made with the Senior Manager of Data Analytics & AI and the CTDO.
Help develop and support AI champion networks across teams and regions, so that good practice spreads beyond individual projects.
Act as a point of contact for use-case and workflow questions from staff, escalating policy questions to the AI Enablement & Learning Platform Lead.
Support responsible use and governance in practice (policy, guardrails and approval workflows owned elsewhere).
Other projects and team coverage (10%)
About You
4–6 years of direct experience in data, product, operations, learning or change, with hands-on experience or demonstrated interest in AI.
Bachelor's degree in Data Analytics, Information Science, Business, Computer Science, Social Sciences or a related field, or equivalent practical experience.
Experience leading or contributing to projects that changed how a team works, such as process improvement, tool adoption or digital transformation.
Using generative AI tools (e.g. LLM-based assistants, custom GPTs or agents) in real workflows, including prompt design, testing outputs and understanding their limitations.
Workflow automation and no-/low-code tools (e.g. Zapier, Make, n8n, or similar), and a working understanding of how APIs and integrations connect systems.
Process mapping and documentation (e.g. Miro, Lucidchart or similar) to capture current and future-state workflows.
Designing measurement approaches: setting baselines, defining success metrics, and running small tests or pilots to compare approaches.
Survey design and qualitative analysis (e.g. interview synthesis, thematic coding).
Profile of someone who would thrive in this role:
Curiosity about AI and how work is changing. You explore new tools and capabilities, experiment with emerging approaches, learn from those experiences, and share what you learn with others.
Systems thinking. You understand how changes to a workflow, team or technology can affect data, time, quality, risk and other parts of an organisation, and you consider those connections when making decisions.
An evidence-first mindset. You approach claims of AI-driven productivity or impact with healthy scepticism, estab