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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.
About the Role
This is a hands-on, systematic role at the intersection of data science and strategic design. You will be responsible for optimising adaptive AI systems while defining the logic through which brands communicate via intelligent interfaces. The remit involves translating high-level brand strategy into executable AI workflows, ensuring data architectures support real-world performance and provide measurable business impact.
You will lead meaningful projects from inception to deployment, bridging the gap between technical rigour and creative intent. We are seeking a practitioner who values the craft of system-building—from the nuance of a system prompt to the robustness of an evaluation framework.
This role defines the next generation of strategy and analytics. We are transitioning from retrospective reporting towards real-time, autonomous orchestration. You will architect the brand’s "logic centre" in an agentic landscape, pivoting from traditional "push" messaging to a model of intent-based pull. Your objective is to define the multidimensional signals—spanning behavioural patterns, historical data, and real-time environmental context—that trigger personalised brand responses. Crucially, you will ensure that as these adaptive communications scale, they remain brand-safe, strategically aligned, and fluidly responsive to user intent.
On any given day, you might:
Lead Execution: Manage the end-to-end execution of adaptive AI experiences and agentic workflows.
Design Behavior: Craft system prompts and intervention protocols that encode brand strategy into AI behavior.
Architect Logic: Develop semantic data models and JSON-LD schemas that make user intent machine-readable.
Route Intelligence: Design decision trees and logic flows that enable intelligent routing and automation.
Audit Discovery: Conduct AI Semantic Information Opportunity (AISO) audits to identify where systems "miss" the brand.
Validate Performance: Design and execute synthetic test scenarios (1,000+ simulated paths) to validate system resilience.
Manage Economics: Monitor operational metrics (latency, cost, accuracy) and optimise system unit economics.
Build Observability: Create dashboards that surface key performance indicators (KPIs) to teams and leadership.
Narrate Strategy: Translate technical performance data into high-level strategic narratives for executive stakeholders.
Collaborate Broadly: Partner with data engineering, strategy, creative, and technology teams to shape the work.
You’d be the right fit if you:
Are AI-Curious: You are fascinated by how AI systems think and behave, seeing workflow design as a core discipline.
Prioritize Intent: Have experience building or optimising digital systems that put user intent first.
Solve Systemically: Bring a clear, structured approach to complex problem-solving and think in patterns, not isolated decisions.
Translate Strategy: Have the ability to turn abstract brand strategy into traceable, executable system logic.
Thrive in Agile: Are comfortable working in a fast-moving, collaborative environment.
Value Craft: Take pride in continuous improvement, performance metrics, and the "fine details" of a system.
Guard the Brand: Understand the tension between dynamic personalisation and brand consistency, ensuring AI systems never 'hallucinate' outside of brand guidelines.
You bring:
Experience: 4+ years in Marketing Sciences, Data Strategy, AI Operations, Creative Technology, or Product Strategy.
Technical Foundation: Basic knowledge of SQL and Python for data manipulation and analysis.
Platform Literacy: Hands-on experience experimenting with LLM platforms (ChatGPT, Claude, Gemini) and an interest in orchestration frameworks like LangChain or LlamaIndex.
Data Comfort: Proficiency in reading and working with JSON / JSON-LD data structures.
Visual Mapping: Working knowledge of workflow and diagramming tools (Figma, Lucidchart, Miro).
Observability Awareness: Familiarity with (or a desire to learn) AI evaluation tools like LangSmith, Weights & Biases, or Arize.
Technical Intuition: A strong understanding of how digital systems work (and fail), and why those failure points matter.
Cross-Functional Track Record: Demonstrated experience working effectively across technical, creative, and business teams.
Bonus:
Prompt Engineering: Familiarity with advanced prompting techniques (Chain-of-Thought, Few-Shot).
Structured Data: Experience building or working with databases, vector stores, or knowledge graphs.
Economic Awareness: Understanding of AI operational costs and performance trade-offs.
Design Systems: Exposure to design systems or pattern-based thinking.
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.