Who we are Oliver Wyman is a general management consulting firm. Quotient - AI by Oliver Wyman brings together deep industry insight, strategic advisory, and hands-on AI delivery to help organizations move from proof to production and from production to enterprise value.
It exists to accelerate AI-enabled business development and help our teams move faster, think differently, and build with reuse in mind.
As Technical Business Partner, you will be WAVE's technical lead and translation point. You will sit at the intersection of consulting and engineering, shaping business needs into technical direction, helping the team prioritise the right work, and turning one-off efforts into reusable assets, platforms, and solutions. This is a senior role for someone who is equally comfortable discussing technical architecture, AI delivery, and commercial opportunity.
Shape technical direction from the outset, ensuring ideas are feasible, scalable, and aligned with the business problem.
Work closely with the Business Analyst to convert incoming demand into the right mix of prioritised work,



technical design, and delivery action.
Recommend infrastructure set-up and go-to-market angles for business development opportunities.
Keep a practical view of the trade-offs between speed, quality, reuse, and commercial value.
Work on AI-enabled, pre-client work that helps our teams win work, strengthen proposals, and create reusable capabilities with real business value.
Build credibility by helping commercial and technical stakeholders align around priorities, trade-offs, and next steps.
Work closely with colleagues across Quotient and the wider firm, learning from both business and technical perspectives.
Work in a way that supports performance, development, and sustainability.
This role is well suited to someone who wants to work at the intersection of consulting, AI, software delivery, and asset creation.
Senior-level experience spanning both business and technical delivery, ideally in a

📌 Oliver Wyman (Madrid)
🏢 Oliver Wyman
📍 Madrid