AI Software Engineer (AWS)
Project – the aim you’ll have
This project focuses on developing solutions that support global organisations in protecting their workforce and ensuring business continuity. It aims to strengthen health, safety, and risk-management capabilities by leveraging modern technology, real-time insights, and preventive strategies. The team works on building reliable, secure, and scalable systems that help companies maintain operational resilience and respond effectively to critical events.
The AI Application Engineer will design and deliver intelligent, AI-enhanced applications using AWS technologies and modern integration patterns. This role focuses on building LLM-driven systems, RAG workflows, and vectorized retrieval architectures within .NET environments. You will also develop MCP server implementations and orchestrate content-intake pipelines integrated with enterprise content management platforms.
- 5+ years of professional experience as an Application Engineer, Software Engineer, or in a similar role working with cloud-based and modern application architectures;
- Proven AI application development (LLM-based systems or RAG implementations);
- AWS architecture and AI service integration (Bedrock, Sagemaker, Lambda);
- MCP server implementation and integration;
- Pipeline design for content intake orchestration with content management systems;
- .NET backend services and API development;
- API design and implementation with .NET frameworks;
- Understanding of AWS products and SDKs;
- System prompt coding for LLM orchestration and control;
- Experience with LangChain, Langfuse, or similar frameworks;
- Vectorization, embedding pipelines, and data retrieval models;
- Front-end development with React or similar modern JS frameworks;
- Familiarity with Sitecore or connected enterprise systems is a plus;
Soft Skills and Experience:
- Clear communication and ability to explain AI and ML concepts to diverse audiences;
- Strong collaboration with data, product, and software engineering teams;
- Analytical approach to AI solution design and performance optimization;
- Adaptable to evolving AI frameworks and cloud-native trends.
