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# Senior Developer - AI Enablement

- **Company:** Henderson Scott
- **Location:** London, UK (Remote available)
- **Experience:** Expert
- **Contract:** Temporary contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Audit Trail, Automation of Tests, Continuous Integration, Information Leak Prevention, Identity and Access Management, Python (Programming Language), Key Management, Live Connect (Windows), Node.Js, OAuth, OpenID, OpenAI, TypeScript, Spring Cloud, Retrieval-Augmented Generation, Large Language Models, Prompt Engineering, Backend, Agentic-AI, Rate Limiting, SC Clearance, Cloudflare, Claude, Evaluation of Large Language Models, Cloudwatch, Model Context Protocol, Terraform, Splunk, Docker, Microservices
- **Published:** November 4, 2026
- **Apply:** https://www.careerboard.com/gb/en/find-jobs-in-United-Kingdom/-7AF2DE82BD2A3FD9B2/

## About the Role

* Strong hands-on experience building production APIs/backend services in Python or TypeScript/Node.js.
 * Practical experience integrating LLM APIs (eg, Anthropic Claude, OpenAI, Mistral) into applications or workflows.
 * Solid understanding of prompt management, structured outputs, tool calling, context handling, and agentic patterns.
 * Experience deploying cloud-native applications on AWS using automated CI/CD and Terraform/Docker.
 * Experience with secrets management, IAM, automated testing, and building observable live services (OpenTelemetry, Splunk, CloudWatch).
 * Active SC Clearance

Desirable Skills:

 * Experience with Cloudflare AI Gateway or custom AI Proxy configurations.
 * Hands-on experience with Model Context Protocol (MCP) or agentic frameworks.
 * Knowledge of RAG, vector databases, embeddings, or LLM evaluation frameworks.
 * Awareness of AI security threats (prompt injection, data leakage, unsafe tool execution).

## Description

* Design, build, test, and maintain Back End microservices and APIs powering the Enterprise AI Gateway.
 * Integrate AWS Bedrock, AI Gateways, and approved foundation-model services into enterprise workflows.
 * Build reusable APIs, libraries, and configuration patterns for consuming teams.
 * Build authentication, authorisation (OIDC/OAuth2), rate limiting, usage attribution, and audit logging controls.
 * Implement safe integrations with AI agents, tool calling, and Model Context Protocol (MCP) services.