Full-Stack Software Engineer (AI Focused)

Job Title: Full-Stack Software Engineer (AI Focused)

Overview:

We are looking for a FullStack Software Engineer that can design, develop, and ship endtoend features that embed large language models (LLMs) and agentic AI into our web and cloudnative platforms. You'll work closely with the cyber and dev teams to create seamless AIpowered 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 microservices that orchestrate LLM calls, prompt pipelines, and tooluse 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 crossbrowser performance; React or Angular expertise is a valuable plus.

- Embed AIdriven 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 (plannerexecutor, toolusing agents) that can act autonomously within defined constraints.

- Evaluate and adopt emerging LLM technologies, RAG (retrievalaugmented generation), and vectorstore solutions.

Collaboration

- Collaborate with team members to design, develop, and integrate AIdriven features, lead rigorous codereview sessions, and champion shared bestpractice 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, welltested code following best practices.