About R/GA

R/GA is an independent creative innovation company built for the intelligence age. We harness the power of design and technology to create more valuable experiences for people and brands. From architecting adaptive brand experiences with AI to optimising complex systems for real-world impact, we help organisations anticipate change and shape what comes next. Our teams combine craft, curiosity and technology to deliver work that drives both business and human impact.

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About the Role

This is a hands-on role for an early-career strategist or analyst who wants to build expertise at the intersection of experience strategy, audience research, measurement, evaluation and Answer Engine Optimisation (AEO). You'll work across both traditional digital products (websites, apps) and generative, AI-driven experiences, as part of a team working out how to make these systems measurable, testable and continuously improvable.

You'll see projects through from audience discovery and ideation to deployment and evaluation, getting hands-on exposure to how human-centred design, technical rigour and strategic thinking come together. We're looking for someone curious, detail-oriented and eager to learn, who enjoys the craft of rigorous testing and wants to grow with a discipline that's still being defined.

Strategy and analytics are moving from retrospective reporting towards real-time, evaluation-driven work. In this role you'll help build the measurement, testing and AEO practices that keep brand experiences visible to answer engines, accurate and validated at scale, and develop skills that are becoming central to the future of the industry.

On any given day, you might:

• Pull Together Audience Research: Gather and synthesise market research and user insights to help build personas and understand user intent.
• Run AEO Audits: Carry out Answer Engine Optimisation audits using established methods, documenting where brand content is missed, misread or misrepresented by AI systems and answer engines.
• Support Experience Strategy: Help turn audience research and user insights into product recommendations, and contribute ideas in ideation sessions for new features, journeys and AI-driven solutions.
• Score AI Outputs: Apply evaluation rubrics to score AI outputs for accuracy, brand alignment and intent-fulfilment, and flag where rubrics could be improved.
• Assist with Testing: Help set up synthetic test scenarios and analyse the results, surfacing edge cases, failure modes and patterns for the wider team to review.
• Work with Structured Data: Support the team in mapping brand content to semantic data models and JSON-LD schema, helping make it machine-readable by AI and answer engines.
• Track Operational Metrics: Monitor and report on latency, cost, accuracy and hallucination rate, flagging notable changes against evaluation benchmarks.
• Build Dashboards & Scorecards: Build and maintain evaluation dashboards and scorecards, and draft initial findings for review.
• Review System Behaviour: Check AI outputs and system prompts against evaluation results to spot where brand strategy isn't coming through as intended.
• Prepare Reporting: Help turn data and insights into clear charts, summaries and slides for clients and stakeholders.
• Collaborate Broadly: Work alongside data engineering, creative and technology teams, learning how each discipline defines and measures "good".