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AI Full Stack Engineer (Contract)

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Remote

AI Full Stack Engineer (Contract)

Harnham

AI Full Stack Engineer (Contract)

Skills

Google Cloud PlatformSQL QueriesDockerTypescriptPythonMachine LearningAIAzure

18 days ago

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Important information


Contract type:

Freelance / Contract

Salary:

£130,000 – £143,000 / year

Location:

London, UK

Work mode:

Remote

Published on:

1 October 2026

What they need


Full Stack AI Engineer (Contract)

MUST HAVE: SC Clearance

£500 - £550 Per Day

Outside IR35

Immediate Start

Fully Remote

The Company

They are a specialist technology organisation delivering AI, software engineering, and data solutions within secure and complex environments. Their work focuses on solving challenging technical problems using modern machine learning and cloud technologies. The team combines deep engineering expertise with a strong focus on innovation, deploying solutions that operate at scale in mission-critical settings.

The Role and Deliverables

  • Design and develop full stack AI applications using Python and TypeScript.
  • Build and enhance frontend interfaces, backend services, APIs, and application architectures.
  • Develop and deploy LLM-powered solutions, including RAG pipelines and agentic AI applications.
  • Integrate and manage SQL and NoSQL data stores, ensuring effective data modelling and system performance.
  • Implement vector databases, semantic search capabilities, and knowledge graph solutions.
  • Take AI products from proof of concept through to production-ready deployment, including secure infrastructure and containerised environments.

Your Skills & Experience

  • Strong experience as a Full Stack AI Engineer or in a similar AI-focused software engineering role.
  • Advanced capability with Python and TypeScript across frontend and backend development.
  • Hands-on experience with LLMs, RAG architectures, agentic AI, and modern AI frameworks.
  • Strong knowledge of APIs, system integration, application architecture, and database technologies.
  • Experience using Docker and deploying AI solutions within cloud environments such as Azure or GCP.
  • Knowledge of vector databases, semantic search, and knowledge graph technologies.
  • Experience deploying AI systems within secure or restricted environments is highly advantageous.
  • Exposure to defence, government, national security, or similarly regulated sectors is beneficial.
  • Active or previously held security clearance is advantageous.

How to Apply

If you're interested in applying your AI engineering expertise to innovative, large-scale projects, please apply with your latest CV.

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