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Remote AI Engineer - London, United Kingdom

Remote AI Engineer London, United Kingdom
Featured Skills:
react node typescript nextjs json
Primary Info:
  • Name: private info
  • Focus: Full Stack
  • Career: Junior, Mid Level
  • Location: London, United Kingdom
  • Timezone:
  • Speaks: English
Actively Looking
  • >= 6 mo contract
  • full time
  • near me
  • remote
All Skills: react node typescript nextjs json Programming & Tooling Python TypeScript R Git Bash uv pyenv Numerical & ML Libraries NumPy Pandas Scikit-learn GenAI & LLM Systems Prompt Engineering Chain-of-Thought Fine-tuning Unsloth vLLM Kiln Agentic Architectures CrewAI LangChain Google A2A OpenAI Agents SDK Model Evaluation & Experimentation Structured eval pipelines test suites LLM judges few-shot testing Cloud & Infra Azure AWS GCP RunPod Supabase Docker Data & Infra Platforms SQL REST APIs Client-Facing & Product Strategy Technical demos pre-sales user research stakeholder communication
Description:
🚀 Founding Contributor - Agent-to-Agent Marketplace (Present, part-time)

In my free time, I'm a founding contributor to an early-stage Agent-to-Agent (A2A) marketplace. It's based on Google's A2A protocol, which is like building the "HTTP for AI agents."

A huge challenge here is framework interoperability. To tackle this, I re-architected a proof-of-concept search agent from the LangGraph framework to the native OpenAI Agents SDK. This not only improved the code's simplicity but also proved our platform could handle agents built with different underlying tech.

I then took this a step further by containerising the full Python agent using Docker and orchestrating a full CI/CD deployment pipeline to Google Cloud Platform (GCP), managing secure API key access with Secret Manager. I also created the first public-facing open-source repository for this work.

🧠 AI Engineer - OpenKit (Present, full-time)

At OpenKit, I design and deploy production-grade LLM systems and multi-agent architectures for various clients.

A project I'm especially proud of is Rubrical (rubrical.ai), an AI-powered marking assistant that we co-developed. It was showcased at London Tech Week and is being adopted by UK schools.

My main challenge is building reliable and trustworthy AI. I lead the evaluation of LLM outputs using structured test suites, few-shot prompting, and model benchmarking with our internal tool, Kiln. I also get to be full-stack, building out AI applications with TypeScript, Supabase, and Flutter on the frontend, and Python for the backend orchestration on platforms like RunPod and OpenRouter.

⚙️ Machine Learning Engineer - Faculty Fellowship

This was a highly competitive program that helps academics like me transition into commercial ML roles.

My challenge was to benchmark and optimise an AI system for generating exam rubrics. I developed a framework to evaluate hundreds of different prompt-engineered configurations. The result? We enabled the automation of marking workflows, reducing marking time by 50% for an AI initiative funded by the UK's Department for Education.

📈 Data & AI Consultant - Covalent Labs UK

I have deep startup experience from my time at Covalent Labs, a $2M+ seed-funded startup where I joined as Employee #1.

The challenge here was wearing multiple hats: I owned key business operations while also developing our agentic data & AI platform. I designed the customer journey and UI/UX, and built custom LangChain scripts to automate market research and define our Ideal Customer Profiles (ICPs).

🏢 Cloud & AI Consultant - Capgemini Invent UK

My career in AI started with a more corporate focus at Capgemini. My main project was to solve the challenge of predicting AI-related expenses for enterprise clients. I built a tool for LLM cost and CO₂ forecasting which was successfully marketed across Capgemini global.
Links:
private info

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