Senior AI Engineer

Build AI-enabled applications and agents 

• Develop AI-driven workflows using large language models, retrieval-augmented generation, prompt orchestration, tool use, and agent frameworks.
• Build reliable integrations between AI agents, APIs, databases, documents, and enterprise systems.
• Implement guardrails, validation logic, fallback handling, and human-in-the-loop controls.
• Evaluate AI outputs using test cases, structured feedback, and measurable quality criteria.

Develop full-stack solutions 

• Build backend services using Kotlin / Java and Spring Boot.
• Create lightweight frontend interfaces using React, SolidJS, TypeScript, or similar technologies.
• Expose AI capabilities through clean, secure, and maintainable APIs.
• Support internal users by making AI solutions accessible, usable, and production-ready.

Integrate with cloud and enterprise platforms 

• Work with Microsoft Azure services, Azure AI Foundry, storage, compute, networking, and monitoring tools.
• Integrate with Entra ID for secure authentication and access control.
• Connect to enterprise platforms such as SharePoint and other internal systems where required.
• Use orchestration and automation tools such as n8n or similar workflow platforms.

Ship and operate production systems 

• Build and maintain CI/CD pipelines and deployment processes.
• Support containerized or cloud-native deployments where required.
• Monitor performance, reliability, cost, latency, and AI output quality.
• Improve solutions iteratively based on real usage and business feedback.

Your golden ticket to the AMINA team:

Required experience 

• Strong full-stack engineering background, ideally with Kotlin / Java, Spring Boot, TypeScript, and React or similar frontend frameworks.
• Hands-on experience with AI engineering concepts such as LLMs, prompting, RAG, agents, embeddings, tool use, or AI workflow orchestration.
• Experience integrating systems through REST APIs, event-driven flows, databases, or enterprise platforms.
• Working knowledge of Microsoft Azure and cloud-based application delivery.
• Practical DevOps experience, including CI/CD, deployment pipelines, monitoring, and troubleshooting.
• Ability to debug across application, integration, cloud, and AI layers.

Helpful experience 

• Azure AI Foundry or similar AI development platforms.
• n8n, Power Automate, LangChain, Semantic Kernel, or similar orchestration frameworks.
• Entra ID, identity integration, and secure access patterns.
• SharePoint, Microsoft 365, or enterprise content systems.
• Kubernetes, containers, observability tools, or infrastructure-as-code.
• Banking, fintech, or another regulated industry.

Mindset 

• Hands-on builder with strong ownership.
• Pragmatic and delivery-focused.
• Curious about fast-moving AI technologies and motivated to keep learning.
• Comfortable working with ambiguity and shaping solutions iteratively.
• Able to explain AI system behavior, limitations, and trade-offs clearly.
  • Collaborative, especially with process engineers and business stakeholders.