Full-Stack Software Engineer (AI Focused)

Job Title: Full-Stack Software Engineer (AI Focused)Overview:We are looking for a Full‑Stack Software Engineer that can design, develop, and ship end‑to‑end features that embed large language models (LLMs) and agentic AI into our web‑ and cloud‑native platforms. You’ll work closely with the cyber and dev teams to create seamless AI‑powered experiences, using both C#/.NET and Python stacks, and leveraging integration frameworks such as .NET Semantic Kernel, OpenAI, and Ollama.Key Responsibilities:Backend Development- Design and build Web Applications, Tools and APIs with ASP.NET Core (.NET Standard) and Python (FastAPI/Flask).- Build micro‑services that orchestrate LLM calls, prompt pipelines, and tool‑use agents.- Integrate with Azure/AWS services, relational and NoSQL databases, and caching layers.Frontend Development- Design and implement responsive, accessible UI components using Bootstrap and jQuery with modern HTML5/CSS3, ensuring clean, modular code and cross‑browser performance; React or Angular expertise is a valuable plus.- Embed AI‑driven widgets (chat, code assist, document summarizer) that interact with backend LLM services.AI/LLM Integration- Embed OpenAI, Ollama, and other LLM providers via the .NET Semantic Kernel and Python SDKs.- Create prompt engineering workflows to enhance the implementation of AI-powered features.- Build agentic AI pipelines (planner‑executor, tool‑using agents) that can act autonomously within defined constraints.- Evaluate and adopt emerging LLM technologies, RAG (retrieval‑augmented generation), and vector‑store solutions.Collaboration- Collaborate with team members to design, develop, and integrate AI‑driven features, lead rigorous code‑review sessions, and champion shared best‑practice patterns that elevate code quality, scalability, and maintainability across the product.We Also Expect You To:- Deliver quickly while maintaining quality and test coverage.- Optimize code for low latency and resource usage.- Continuously learn and share new AI/ML knowledge.- Quickly adopt and apply new tools and technologies.- Produce clean, modular, well‑tested code following best practices.