LLM/.NET Software Engineer
Indexed description
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.
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.
- 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 similar).
- BS/MS in Computer Science, Engineering, or a related field.
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