Key Responsibilities • Develop, integrate, and support GenAI-powered solutions using Python and .NET frameworks. • Collaborate with engineering teams to address real-world challenges using LLMs (as consumers, not model creators). • Apply deep problem-solving skills to engineer solutions — not just propose architectures. • Scale AI models for enterprise-level performance, considering optimization, tokenization, and cost efficiency. • Justify and implement tokenizer strategies and other AI engineering techniques for better model utility. • Work cross-functionally with product owners, data scientists, and cloud engineers to deliver impactful GenAI solutions. • Remain current with industry best practices and GenAI trends, adapting solutions accordingly. Required Skills & Qualifications • 5+ years of software engineering experience with a strong focus on Python development. • Solid working knowledge of .NET framework (C# or ASP.NET). • Demonstrated experience in delivering solution-oriented AI implementations (not just model development). • Hands-on experience with LLMs (e.g., OpenAI, Azure OpenAI, HuggingFace) in real-world applications. • Strong understanding of tokenization, inference strategies, and model scaling principles. • Ability to explain and justify engineering decisions to both technical and non-technical stakeholders. • Comfortable working in agile, cross-functional environments with high accountability. Nice To Have • Familiarity with cloud-based AI/ML environments (Azure preferred). • Exposure to MLOps practices and deployment pipelines. • Experience with prompt engineering, embedding models, or retrieval-augmented generation (RAG) Skills: genai,cloud-based ai/ml environments,mlops practices,solution-oriented ai implementations,accountability,python,agile methodologies,tokenization,ai engineering,llms,azure,cloud,.net