AI Product and Research Engineer

ZipRecruiter; London; On-site; GBP 65,000 - 90,000; Full time

Job summary

A leading trading platform seeks a talented engineer for its new AI department in London. The role involves developing cutting-edge AI solutions, integrating APIs, and creating rapid prototypes to enhance their award-winning products. Ideal candidates have a master's degree in AI or Computer Science, with proven skills in prompt engineering and strong Python proficiency. Join a driven team dedicated to pushing technological boundaries.

Qualifications

• Hands-on experience integrating LLM APIs (OpenAI, Hugging Face).
• Deep expertise in prompt engineering and tooling.
• Proven skills in rapid prototyping using Streamlit or similar.

Responsibilities

• Craft, iterate, and optimize prompts for APIs.
• Implement CI/CD pipelines and model monitoring.
• Create interactive AI demos with Streamlit and Gradio.

Skills

Prompt Engineering

Rapid Prototyping

Python

MLOps

Communication

Education

Master’s degree in AI and/or Computer Science

Tools

Docker

Kubernetes

LangChain

LlamaIndex

Streamlit

Job description

Job Description

We are a leading trading platform that is ambitiously expanding to the four corners of the globe. Our top-rated products have won prestigious industry awards for their cutting-edge technology and seamless client experience. We deliver only the best, so we are always in search of the best people to join our ever-growing talented team.

We’re spinning up a brand-new AI department and need a first-on-the-ground engineer who can turn wild LLM ideas into working demos overnight, teach everyone around you why automation matters, and have fun doing it.

If you can ship Python or TypeScript prototypes before the pizza gets cold, keep reading.

Responsibilities:

• Prompt Engineering & Orchestration: Craft, iterate, and optimize prompts for APIs (OpenAI, Cohere, Anthropic). Build multi-step “chains” using LangChain, LlamaIndex, or custom controllers. Develop and maintain AI microservices using Docker, Kubernetes, and FastAPI, ensuring smooth model serving and error handling;
• Vector Search & Retrieval: Implement retrieval-augmented workflows: ingest documents, index embeddings (Pinecone, FAISS, Weaviate), and build similarity search features.
• Rapid Prototyping: Create interactive AI demos and proofs-of-concept with Streamlit, Gradio, or Next.js for stakeholder feedback;
• MLOps & Deployment: Implement CI/CD pipelines (e.g., GitLab Actions, Apache Airflow), experiment tracking (MLflow), and model monitoring for reliable production workflows;
• Cross-Functional Collaboration: Participate in code reviews, architectural discussions, and sprint planning to deliver features end-to-end.

Requirements:

• Master’s degree in AI and/or Computer Science;
• Hands-on experience integrating LLM APIs (e.g. OpenAI, Hugging Face Inference);
• Practical experience fine-tuning LLMs via OpenAI, HuggingFace or similar APIs;
• Strong proficiency in Python;
• Deep expertise in prompt engineering and tooling like LangChain or LlamaIndex;
• Proficiency with vector databases (Pinecone, FAISS, Weaviate) and document embedding pipelines;
• Proven rapid-prototyping skills using Streamlit or equivalent frameworks for UI demos.
• Familiarity with containerization (Docker) and at least one orchestration/deployment platform;
• Excellent communication and ability to frame AI solutions in business terms.

Nice-to-have:

• Familiarity with database systems (PostgreSQL, MongoDB) and caching layers (Redis);
• Open-source contributions or published AI demos;
• Understanding of cost-optimization, monitoring for LLM usage and model-API trade-offs;
• Familiarity with prompt engineering best practices and “vibe-coding” tools (e.g., GitHub Copilot, Cursor IDE);
• Willingness to travel occasionally for team offsites or workshops.