AI Product Engineer
We are looking for an experienced AI Product Engineer to help build and scale AI-powered features within a modern product environment. This is a hands-on engineering role focused on integrating commercial AI APIs into a .NET ecosystem — not building models from scratch.
You will design, develop, and deliver production-ready features that rely on services such as Anthropic Claude, AWS Bedrock, and OpenAI. AI-assisted development will be a core part of your workflow, and you will help shape how it is adopted across the engineering team.
This role is ideal for someone who has already worked in a team where AI was embedded into real products and can bring proven patterns, practices, and standards into a new environment.
What You’ll Do- Design and implement AI-powered product features within a C# / .NET stack
- Integrate commercial AI APIs into production systems with reliability and scalability in mind
- Establish best practices for AI integration across the codebase
- Lead by example through AI-assisted development workflows
- Pair with developers and support adoption of tools like Claude Code or Cursor
- Build observable, maintainable systems with strong logging, cost tracking, and guardrails
- 5+ years experience with C# / .NET Core
- 7+ years total commercial software engineering experience
- Proven experience designing and shipping AI API integrations in production (.NET)
- Experience setting patterns that other developers adopted across a team
- Hands-on experience introducing AI-assisted development tools into a team environment
- Strong RESTful API design skills (clean, versioned, observable)
- Solid SQL experience (MariaDB or MySQL)
- Focus on quality, resilience, and observability in AI-driven features
- AWS experience (EC2, RDS, Lambda, S3, Bedrock)
- Product-level prompt design and iteration practices
- Experience with structured outputs, tool use, or function calling
- Frontend exposure (JavaScript, Vue, Nuxt 3)
- Microservices or distributed systems experience
- Familiarity with Shape Up methodology
- Awareness of secure-by-design principles (e.g. ISO 27001)
- Focus on training models rather than integrating them
- Come from a data science background without strong engineering experience
- Prefer Python-heavy environments and do not want to work in .NET
- Are sceptical of AI-assisted development
- Have not worked with paid AI APIs in production
- Are looking for a strategy or leadership-only AI role
If you’re passionate about building real-world AI features and want to work in a team where AI is part of the engineering craft — not just a concept — we’d love to hear from you.
Benefits:- Hybrid working - 2 days office based
- Training and Development budget
- Excellent career progression