AI Full Stack Engineer

Cedar Technology is recruiting for an AI Full Stack Engineer opportunity within an investment organisation undergoing an ambitious AI transformation.

Rather than joining a large engineering function to maintain existing systems, you’ll become part of a small, highly influential AI team, working directly with senior stakeholders to design, develop and deploy intelligent applications across the business.

The organisation is investing in becoming AI native, with opportunities spanning investment processes, enterprise automation, data workflows and the wider application of agentic AI.

This is a role for someone who wants to build, experiment, influence technical strategy and take genuine ownership of what they deliver.

You’ll work across the full AI engineering lifecycle, from identifying valuable use cases and making architectural decisions through to building, deploying and improving systems that people actually use.

The engineering challenge

You’ll work closely with the Head of AI, contributing both hands-on engineering expertise and technical judgement to a growing portfolio of AI initiatives.

Your responsibilities will include:

• Building agentic AI applications: Design and develop intelligent agents, multi-step workflows and AI-powered tools that automate complex business processes.
• Engineering LLM-powered solutions: Develop production-ready applications using modern language models, including Anthropic’s Claude ecosystem.
• Developing AI integrations: Build and evaluate integrations using Model Context Protocol (MCP), APIs and enterprise data sources.
• Designing retrieval and context systems: Apply RAG, embeddings, prompt engineering and context engineering to improve the accuracy and usefulness of AI applications.
• Establishing evaluation and reliability: Implement appropriate testing, evaluations, guardrails and monitoring to ensure applications behave as expected.
• Connecting AI with enterprise data: Work alongside data and IT teams to integrate AI capabilities with Microsoft technologies, Azure and Fabric.
• Influencing technical architecture: Contribute to decisions involving AI tooling, vendor selection, security, scalability and build-versus-buy considerations.
• Driving AI adoption: Collaborate with non-technical teams to identify opportunities, develop useful solutions and help colleagues use AI effectively., The remit includes LLMs, agentic workflows, MCP integrations, AI-assisted software development and the practical challenges of implementing reliable intelligent systems.

1. Visibility and influence

Working within a small AI team means collaborating closely with business leaders and influencing initiatives that extend across multiple functions.

1. An organisation investing in AI transformation

This is an opportunity to help an established business evolve its operating model around new technological capabilities, rather than simply adding AI features to an existing product.

1. Work with a purpose

Your engineering expertise will contribute to an organisation operating within investment, connecting advanced technology with work intended to generate positive outcomes.

We’re interested in engineers who combine strong software engineering fundamentals with practical experience developing and deploying AI applications., * Strong Python programming and broader full stack engineering capability.

• Demonstrable experience building and shipping software products that people genuinely rely on, including AI or agentic applications.
• Practical understanding of LLMs, generative AI and modern AI development techniques.
• Experience with prompt engineering, RAG, embeddings or agent-based workflows.
• An understanding of model evaluation, reliability and the security considerations involved in AI deployment.
• Confidence making technical architecture decisions and explaining the reasoning behind them.
• Ability to take ownership from initial problem discovery through to delivery and iteration.
• Strong communication skills and the ability to work directly with non-technical stakeholders.

Particularly interesting experience

• Anthropic Claude, Claude Code or other AI-assisted development environments.
• Model Context Protocol (MCP), tool calling and agent orchestration.
• Microsoft Azure, Fabric, SharePoint, Graph API or Power Automate.
• AI evaluation frameworks, guardrails and context management.
• Enterprise automation, data pipelines and API integrations.
• Experience working in a small engineering team with significant autonomy., * Engineering Execution: How do you approach reliability, evaluation, security and scalability?
• Needs Alignment: How does your experience translate to the organisation’s engineering challenges?

We believe exceptional AI Engineers should be assessed on their ability to solve real problems, not simply the number of frameworks listed on their CV., If you’re an experienced software engineer who has successfully built AI applications and wants the opportunity to influence an organisation’s AI strategy through hands-on delivery, we’d welcome a confidential conversation.

You don’t need previous investment industry experience, but you should have genuine curiosity about how AI can improve the way organisations work.

Candidates must have the existing right to work in the UK. Visa sponsorship is not available for this opportunity.

United Kingdom £200000 - £250000 US$200000 - US$250000 per annum + Discretionary, additional to base GBP / Year

At Cedar Technology, we specialise in recruiting across Applied AI, Machine Learning, AI Engineering and ML Infrastructure.

We understand the difference between engineers who have experimented with LLM APIs and those who can design, build and maintain intelligent systems that deliver dependable results.

Our approach focuses on six key areas through our PROVEN assessment framework:

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