GenAI Prototyping Specialist

Location: Central London (Hybrid Onsite - Tuesday/Wednesday/Thursday)

Role Summary

We are looking for a GenAI Prototyping Specialist to be embedded within Fractal's EMEIA team, focused 100% on new capability development. This is not a reporting or maintenance role - it is a fast paced, innovation first position where you will rapidly conceptualise, build, and iterate on proof of concept AI solutions using cutting edge LLM tooling.

Key Responsibilities

• Rapidly concept, build, and iterate on proof of concept GenAI solutions, leveraging LLM tooling including Claude Code, client specific LLM platforms and tools.
• Generate and evaluate new POC ideas aligned with client priorities, identified in weekly sessions with the Fractal lead and client stakeholders.
• Progress high value POCs from initial concept through to business prototype stage, suitable for stakeholder demonstration.
• Apply product intuition to prioritise concepts with the highest business impact and scalability.
• Attend in person working sessions at the client's London office on Tuesdays, Wednesdays, and Thursdays.
• Participate in daily/weekly sync sessions with the Fractal Engagement Manager, align on priorities, share progress, and incorporate feedback.
• Present prototypes and technical approaches to client stakeholders, articulating business value and technical underpinnings.
• Document prototypes, technical approaches, architectural decisions and outcomes in a form suitable for handoff into the client's global product pipeline.
• Prepare a showcase deliverable for mid June 2026, presenting selected POCs to client stakeholders including global leadership.
• Create lightweight technical documentation enabling other engineers to understand, extend, or productionise prototype solutions.

Required Qualifications

• 5+ years of professional experience in software engineering, ML engineering, or applied AI development.
• Strong proficiency in Python for rapid prototyping, data manipulation, API integration and ML model experimentation.
• Hands on experience with GenAI/LLM application development - prompt engineering, RAG architectures, tool use and agentic workflows.
• Experience using AI assisted coding tools such as Claude Code, GitHub Copilot or Cursor.
• Working knowledge of ML fundamentals: classification, regression, clustering, NLP, embeddings and model evaluation.
• Ability to move from idea to working prototype quickly, comfortable with imperfect code and fast iteration.
• Strong communication skills - demo prototypes, explain technical concepts to non technical stakeholders, articulate the "so what" of each solution.
• Self directed and adaptable - comfortable working without detailed specifications in a fast changing environment.

Preferred Qualifications

• Experience with multiple LLM providers and platforms (Anthropic Claude, OpenAI, open source models via Hugging Face).
• Front end development familiarity (React, HTML/CSS, Streamlit, Gradio) for building interactive demo interfaces around AI prototypes.
• Experience with cloud AI services (Azure OpenAI, AWS Bedrock, GCP Vertex AI) for model hosting and API integration.
• Background in marketing technology, digital marketing or consumer facing product development.
• Embedded consulting or contractor experience within large enterprise environments.
• Familiarity with vector databases (Pinecone, ChromaDB, Weaviate) and semantic search architectures.
• Previous experience building and presenting POCs or demo prototypes to senior/executive stakeholders.
• Experience with multi agent frameworks (LangGraph, AutoGen, CrewAI) or workflow orchestration tools.

Engagement Model & Working Arrangement

• Employment Type: Fractal FTE, embedded within the client's EMEIA team at the client's London office.
• Primary Location: Client office, Central London.
• In person days: Tuesday, Wednesday, Thursday each week.
• Remote days: Monday and Friday (flexible).

Education

• Bachelor's degree in Computer Science, Data Science, Machine Learning, Software Engineering or a related technical field.
• Master's degree is a plus but not required.
• Self taught engineers with strong portfolios and proven prototyping ability are welcome.