Applied AI Engineer Remote, Full-Time , PK AS221 - Smart Working

About Smart Working

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About the Role

We are hiring an Applied AI Engineer to design and build an AI-powered system that automates the generation of technical reports for insurance claims. This is a highly practical, product-focused role where success is defined by delivering a working, production-ready solution that integrates into real business workflows.

The current process is manual and relies on engineers reviewing fragmented data across multiple sources, including documents, images, videos, and historical reports. The goal is to create an end-to-end AI solution that can process this unstructured data, retrieve relevant context, and generate accurate, structured outputs.

You will work with LLM-based systems, such as retrieval-augmented generation (RAG) pipelines, to build scalable solutions that integrate with existing systems. This role requires a strong builder mindset, the ability to work with messy data, and the confidence to operate in an environment with evolving requirements.

In addition to delivery, you will help guide the organisation in adopting AI, communicating clearly with stakeholders and shaping how AI solutions are implemented across the business.

Responsibilities

• Design and implement end-to-end AI solutions for document understanding and automated report generation.
• Build and deploy LLM-based systems, including RAG pipelines, to retrieve and combine context from multiple data sources.
• Work with unstructured and semi-structured data such as PDFs, documents, images, and historical records, transforming it into usable inputs for AI systems.
• Rapidly prototype, test, and iterate on AI solutions to deliver measurable improvements.
• Integrate AI outputs into existing systems via APIs, collaborating with backend teams working in C# and SQL Server environments.
• Ensure solutions are scalable, reliable, and aligned with real-world business workflows.
• Address performance, accuracy, and usability challenges in AI-generated outputs.
• Operate within data privacy and security constraints, including handling sensitive information and exploring lo