AI Software Engineer – C# .NET

Apache Associates are currently working with an innovative SaaS organisation that is investing heavily in AI across its products. We’re looking for an AI Software Engineer with strong C# .NET experience to join the team and help turn emerging AI capabilities into genuine, production-ready product features.

This is an ideal opportunity for a developer who combines strong software engineering fundamentals with hands-on LLM experience and enjoys working in an environment where things move quickly.

You’ll be taking AI concepts from initial idea and experimentation through to fully integrated, evaluated features within established .NET products.

The Role

You’ll be responsible for building AI-powered capabilities across the product portfolio, working with LLMs, prompt engineering, context design and structured outputs , while ensuring everything you build is robust enough for production.

You’ll be expected to prototype quickly, but equally importantly, understand where engineering discipline is essential. That means thinking about accuracy, reliability, latency, cost, monitoring, fallbacks and evaluation rather than simply getting an AI feature to work in a demo.

You’ll work closely with existing engineering teams, Product Managers, Product Owners and subject matter experts to understand the business problem before deciding on the technical solution.

Key Responsibilities

Design and build prompts, context strategies and LLM integrations for real-world product features. Develop primarily in C# .NET , integrating AI capabilities into established codebases. Build production-grade AI services with appropriate error handling, fallbacks, monitoring and logging. Prototype new ideas quickly and turn successful experiments into robust production features. Develop structured approaches to evaluating LLM outputs , using real business scenarios and measurable results. Work with LLM APIs across different providers and make pragmatic decisions around quality, cost and latency. Use AI coding tools such as GitHub Copilot, Cursor or equivalent as part of your day-to-day development. Work alongside existing engineering teams to ensure your solutions fit established coding standards, architecture and deployment pipelines. Keep pace with the rapidly changing AI ecosystem and share new approaches and learning with colleagues. Work with Product and subject matter experts to understand the underlying business problem rather than simply responding to a technical requirement. Ensure AI features are developed with appropriate consideration for accuracy, safety and data handling .