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Loading LAYIQ…From rga's posting. “We” and “our” refer to the employer.
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.
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.
Gather and synthesise market research and user insights to help build personas and understand user intent.
Carry out Answer Engine Optimisation audits using established methods, documenting where brand content is missed, misread or misrepresented by AI systems and answer engines.
Help turn audience research and user insights into product recommendations, and contribute ideas in ideation sessions for new features, journeys and AI-driven solutions.
Apply evaluation rubrics to score AI outputs for accuracy, brand alignment and intent-fulfilment, and flag where rubrics could be improved.
Help set up synthetic test scenarios and analyse the results, surfacing edge cases, failure modes and patterns for the wider team to review.
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.
Monitor and report on latency, cost, accuracy and hallucination rate, flagging notable changes against evaluation benchmarks.
Build and maintain evaluation dashboards and scorecards, and draft initial findings for review.
Check AI outputs and system prompts against evaluation results to spot where brand strategy isn't coming through as intended.
Help turn data and insights into clear charts, summaries and slides for clients and stakeholders.
Work alongside data engineering, creative and technology teams, learning how each discipline defines and measures "good".
Enjoy understanding what audiences need and why, and want to see that insight shape digital products and AI experiences.
Find it genuinely interesting to dig into how AI systems succeed and fail, and see testing as a core part of good work.
Are interested in how content and brand signals are discovered and surfaced by AI and answer engines, and keen to build expertise in measuring it.
Approach problems methodically, ask good questions and aren't afraid to share ideas.
Take care over accuracy, and like making sure numbers, criteria and findings hold up.
Are comfortable in a fast-moving, iterative environment where priorities shift and you learn by doing.
Welcome feedback, learn quickly and want to take on more responsibility over time.
Understand why brand consistency matters, and are interested in how to catch AI "hallucinations" before they reach users.
Experience with research, analytics, measurement, marketing sciences or a related field. Exposure to generative AI products or evaluation is a plus but not essential.
Some experience with qualitative or quantitative research methods, such as surveys, interviews, desk research or audience analysis.
An interest in product, CX or UX strategy, and in how audience insight informs product and channel decisions.
Working knowledge of SQL, Python or similar for data analysis, or strong spreadsheet skills and a clear willingness to build technical skills.
Hands-on familiarity with LLM platforms (ChatGPT, Claude, Gemini, Perplexity) and a genuine interest in how they surface, cite and rank content.
Comfort working with data in different forms, including structured formats like JSON, and turning it into clear, accessible charts and summaries.
Some experience with Figma, Miro, Lucidchart or similar for mapping journeys, processes or logic.
The ability to explain findings clearly in writing and in conversation, to colleagues from different disciplines.
Exposure to AI evaluation or observability tools such as LangSmith or Arize.
Awareness of agentic workflows or orchestration frameworks such as LangChain or LlamaIndex.
Familiarity with prompting techniques such as Chain-of-Thought and Few-Shot.
Some grounding in A/B testing, experiment design or basic statistical methods.
Any exposure to schema markup, JSON-LD, databases or knowledge graphs.
Experience with SEO or content work and an interest in how it applies to answer engines.
You'll work closely with experienced strategists on real client work in one of the fastest-evolving areas of the industry, building practical skills in measurement, AI evaluation and AEO alongside the strategic thinking that ties it all together.
This role is based in London and requires in-office collaboration three days per week: Wednesday, Thursday, and one additional day of your choice. Candidates must be located in the London area or willing to relocate before their start date.
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