The Company
Wizeline is a global digital services company helping mid-size to Fortune 500 companies build, scale, and deliver high-quality digital products and services. We thrive in solving our customer’s challenges through human-centered experiences, digital core modernization, and intelligence everywhere (AI/ML and data). We help them succeed in building digital capabilities that bring technology to the core of their business.
Your Day-to-Day
Here's what you'll be doing in your day-to-day work:
- Design and build secure, scalable .NET applications powered by LLMs and Azure AI services.
- Develop AI-enabled solutions using Azure OpenAI , Azure AI Search , and Retrieval-Augmented Generation (RAG) .
- Own features end-to-end, from discovery and proof of value through implementation and production readiness.
- Collaborate with Product, Platform, Data, Security, Risk, Compliance, and business stakeholders to deliver AI solutions in regulated environments.
- Build reusable, reliable, and cost-efficient cloud-native services on Microsoft Azure .
- Ensure AI solutions are explainable, auditable, secure, and aligned with engineering best practices.
- Contribute to improving development standards, code quality, and technical innovation across the team.
- Work on impactful projects that leverage Generative AI to automate workflows, improve operational efficiency, and deliver measurable business value.
Are You a Fit?
Sounds awesome, right? Now, let’s make sure you’re a good fit for the role.
Must-have Skills
- Strong experience developing applications using C# and .NET (.NET Core / .NET 6+) .
- Experience building secure, scalable, enterprise-grade backend applications.
- Hands-on experience developing and consuming REST APIs .
- Experience with Microsoft Azure , including App Services, Azure Functions, and cloud-native architectures.
- Practical experience building applications using Azure OpenAI Service for chat and completion capabilities.
- Experience with Azure AI Studio / Azure AI Foundry .
- Experience implementing Retrieval-Augmented Generation (RAG) solutions.
- Hybrid retrieval
- Semantic ranking
- Citation-backed responses
- Understanding of when to leverage RAG versus prompt engineering or fine-tuning .
- Document chunking
- Indexing
- Embeddings/vectorization concepts
- Knowledge of prompt engineering best practices and responsible AI principles.
- Experience working with SQL and relational databases.
- Understanding of secure software development and cloud security best practices.
- Ability to collaborate effectively with Product, Data, Security, Compliance, and business stakeholders.
- Strong communication skills in English.