Oliver Wyman – AI Engineer (m/f/d) – Quotient AI Specialist – Madrid / London

Overview

As an AI Engineer in the WAVE team, you turn briefs into working AI prototypes and production-ready solutions, focusing on agent- and LLM-based work alongside traditional ML where appropriate. You will contribute across software and data science disciplines to build reusable, scalable AI-enabled outputs that support business development and project delivery. You’ll collaborate with Quotient Inside, platform/infrastructure teams, and client-facing colleagues to move ideas from experiment to impact. This role places you at the forefront of practical AI delivery in a consulting setting.

Pay / Benefits

• Learning and visibility in a newly created team
• Pilot project with scale potential
• Hybrid work arrangement with office presence three days a week
• Collaborative, inclusive culture
• Opportunity to shape a new capability from the ground up
• Performance, development, and sustainability focus

Responsibilities

• Build AI agent and LLM-based solutions to support business development and project execution
• Develop traditional ML and analytical models where suitable
• Prototype disruptive delivery formats (agents, avatars, visual formats) to reduce slides/meetings
• Build with reuse and scale in mind; coordinate with Quotient Inside for productization
• Translate business needs into technical execution with the Technical Business Partner
• Collaborate with Platform/Infrastructure Engineer to deploy solutions reliably
• Pair with Front-end / AI Content Creator on client-facing outputs
• Join client discussions to demonstrate technical credibility
• Help the team move quickly from experiment to delivery while maintaining quality

Key requirements

• Fluency in Python and modern AI/ML tooling across the build lifecycle
• Hands-on experience shipping LLM-based or ML solutions under time pressure
• For data-science-leaning track: strong ML maths (statistics, linear algebra) and modelling techniques
• For software-engineering-leaning track: strong engineering practice (testing, code hygiene, deployment)
• Ability to make practical design decisions quickly and keep moving
• Experience building solutions useful in real-world settings, not only experiments
• Full professional English
• Spanish welcome

• Practical decision-making under time pressure
• Cross-functional collaboration
• Clear communication and technical storytelling
• Python proficiency
• ML/AI tooling across build lifecycle
• LLM-based solutions and agent frameworks

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