LLM/.NET Software Engineer

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:

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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.

Strong understanding of Azure AI Search , including:

Hybrid retrieval

Semantic ranking

Citation-backed responses

Understanding of when to leverage RAG versus prompt engineering or fine-tuning .

Experience preparing knowledge sources for AI retrieval, including:

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.

Nice to have Skills

Experience working in Financial Services, Banking, FinTech, or Financial Crime (FinCrime) domains.

Familiarity with AI use cases such as:

KYC / KYB

Name Screening

Transaction Monitoring

Fraud Detection

Cross Border Payments

Case Investigation

Experience evaluating different LLM providers and understanding trade-offs between Azure OpenAI and other foundation models.

Familiarity with frameworks such as LangChain, Semantic Kernel, or similar orchestration frameworks .

Experience with vector databases and modern AI application architectures.

Experience with Docker, Kubernetes, and DevOps practices.

Knowledge of CI/CD pipelines and Infrastructure as Code.

Experience implementing automated testing (xUnit, NUnit, or simil