AI .NET
Vor 2 Tagen
- You own the end-to-end development lifecycle for new gen-AI services and integrations with other systems.
- You will collaborate closely with engineers, systems architects, product managers and internal customers to understand their problems and implement effective solutions.
- You will work with product teams to share relevant feedback and iterate on relentlessly improving product value.
- You will build, release and maintain Azure pipelines, ensuring they meet security requirements at every stage.
- You have 5+ years of professional engineering experience (excluding internships) in relevant roles in tech and product-driven teams.
- You love collaborating across teams and working at the boundary of engineering and research.
- You have experience with the systems and frameworks used creating low-latency genAI apps involving RAG-based workflows, vector databases, and integration of various kinds of data sources with AI models; experience with small/local language models is a plus.
- You possess knowledge of prompt engineering and best practices for working with large language models, including tailoring prompts to different model families (e.g. GPT, LLaMA, Mistral), with additional experience in evaluating, documenting and reporting the performance of LLM-based AI systems being a plus.
- You are proficient in developing cloud applications (Azure, Kubernetes) using .NET/C# and ASP.NET Core with familiarity with Azure OpenAI or similar services and you have experience with building and maintaining CI/CD Pipelines with Azure DevOps or similar infrastructure as well as infrastructure as Code (IaC) tools such as Terraform or Bicep (with Terraform preferred) for managing Azure cloud environments.
- You have experience working with GraphQL (ideally using HotChocolate), TypeScript, React, and/or other web technologies, MongoDB and relational databases.
- You excel at effectively navigating through loosely defined tasks and managing competing priorities or deadlines.
- You bring experience with Python; understanding how deep learning works is a plus.
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