Building production-grade AI applications and turning complex business challenges into practical, scalable solutions.
Working with C#/.NET, Azure and modern LLM technologies.
Collaborating with product, engineering, QA, UX and business stakeholders.
Raising AI engineering capability across the wider technology team through coaching, practical standards and technical leadership.
Shipping meaningful AI-enabled products in short iterations, learn from real usage and continuously improve quality.

Strong ability in C# and .NET building production applications and services.
Writing and using unit tests, using any language and test framework.
Microsoft Azure and deploying cloud-based applications in production environments.
Hands-on experience implementing LLM-driven applications beyond experimentation or demos.
Able to explain and apply LLM evals as a core quality discipline for AI applications.
Familiarity with OpenAI-compatible APIs, protocols, or SDKs, and the practical considerations of integrating them into applications.
Clear understanding of RAG and the role of vector embeddings in retrieval-based AI systems.
Strong understanding of software testing fundamentals, including unit, integration, and end-to-end testing, and how these differ from AI-specific evaluation.
Numerical confidence and working familiarity with concepts such as similarity, clustering, PCA, and basic linear algebra.
Full product delivery mindset focused on user value, reliability, and measurable quality.
Comfortable working with ambiguity, rapid iteration, and shifting priorities.
Strong communication skills and ability to work effectively with technical and non-technical stakeholders.

Senior AI Engineer

Key skills