Full‑Stack Applied AI Engineer (Agentic AI)

Job Description:

We are seeking a Full-Stack Applied AI Engineer to build and deliver production-grade, AI-powered applications. This role focuses on applied AI, including agentic systems, and involves integrating Large Language Models (LLMs) into real-world applications using modern frontend, backend, and Azure cloud technologies.

The ideal candidate is a delivery-oriented developer with a strong foundation in full-stack development and a passion for applying AI to solve business problems.

Key Responsibilities End-to-End Development: Own the design, development, and deployment of AI-enabled full-stack applications. AI Integration: Build and integrate AI-driven features using LLMs, prompt engineering, Retrieval-Augmented Generation (RAG), and function/tool-calling. Frontend Development: Develop responsive and intuitive user interfaces using React. Backend Development: Build secure, scalable backend APIs and services using C# / .NET. Cloud Deployment: Deploy, manage, and monitor applications on Microsoft Azure, utilizing services like App Services, Azure OpenAI, and Azure Functions. DevOps & Quality: Implement and maintain CI/CD pipelines, automated testing, and observability to ensure system reliability and performance. Collaboration: Partner closely with product managers, UX designers, and business stakeholders to translate requirements into technical solutions.

Required Skills Frontend

• React (mandatory)
• Flutter (preferred)

Backend

• C# / .NET
• REST API design and integration

Applied AI

• Hands-on experience with LLMs and prompt engineering
• Experience building or integrating agentic AI workflows
• Familiarity with RAG, vector databases, LangChain-like frameworks

Cloud & DevOps

• Microsoft Azure (App Services, Azure OpenAI, Functions, Storage, etc.)
• Azure DevOps CI/CD
• Docker (AKS is a plus)

Good to Have

• Experience with Azure OpenAI or similar AI platforms
• Python or Node.js for AI orchestration
• Experience integrating AI into enterprise/business systems
• Exposure to AI-assisted development tools and workflows

Soft Skills

• Strong problem-solving and ownership mindset
• Ability to translate business problems into practical AI solutions
• Clear communication with technical and non-technical stakeholders