KI-Ingenieur

Supporting the ongoing digital transformation and innovation initiatives within a dynamic enterprise environment, the AI Engineer will design, develop, and implement cutting-edge Artificial Intelligence (AI) and Machine Learning (ML) solutions aimed at enhancing operational processes and delivering measurable business improvements. This role exists to embed AI capabilities across enterprise applications, leveraging advances such as Large Language Models (LLMs) and Agentic AI to elevate productivity, streamline workflows, and enrich user experiences while maintaining robust data governance and security compliance.

The AI Engineer is central to supporting efficient digitalisation strategies by collaborating with both technical teams and business stakeholders to identify AI-driven opportunities and translate these into scalable solutions. Responsibilities extend from the initial design to deployment and ongoing maintenance of AI applications, with a focus on integrating these through APIs into existing and future systems. A significant part of the role involves developing sophisticated AI Agent workflows and Retrieval-Augmented Generation (RAG) solutions leveraging frameworks like LangChain and LangGraph, positioning the organisation at the forefront of emerging AI technologies.

Day-to-day activities include preparing and managing diverse datasets needed for model training and evaluation, working closely with vector databases and semantic search technologies to optimise AI responses. The role requires hands-on experience with major AI platforms and cloud deployment tools, including the Azure AI Service ecosystem and OpenAI APIs, alongside containerisation using Docker and version control via Git. Ensuring solutions are secure, compliant, and align with enterprise governance policies is an essential ongoing responsibility.

The AI Engineer will also contribute to proof-of-concept exercises and technology assessments, keeping abreast of industry trends to continually enhance AI application effectiveness and introduce innovative features. Collaboration with stakeholders spans various business domains, including HR systems such as payroll, Time & Attendance, and enterprise business applications, where the successful candidate will provide technical insight, user support, and detailed documentation.

A solid technical background is required, with a degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or related fields. Candidates should bring at least two to three years of relevant experience developing AI and ML solutions, particularly in Agentic AI and LLM-based applications. Expertise in prompt engineering, AI model optimisation, and knowledge of AI frameworks such as TensorFlow and PyTorch is key. Familiarity with integration patterns using REST APIs and proficiency in Python are essential to effectively bridge AI technologies with existing business systems.

Experience with cloud-native AI platforms, particularly Microsoft Azure’s AI capabilities and OpenAI services, is crucial—candidates will be expected to deploy and maintain AI applications within these environments while managing containerised deployments and code repositories. While direct experience with HRIS or payroll enterprise systems is advantageous, candidates with a strong grasp of enterprise workflows, business process automation, and AI system integration will thrive.

The role demands excellent analytical skills, autonomy in managing projects, and the ability to work collaboratively within a cross-functional team. Given the rapid pace of AI innovation, a proactive approach to learning and adapting to new tools and methodologies is vital for long-term success.

This position is full-time and requires working onsite, contributing directly to the enterprise’s core AI infrastructure and its transformation objectives. The remit covers a broad spectrum of AI-powered business improvements, ensuring the organisation remains at the cutting edge of digital capability.

This role sits within an industry sector focused broadly on artificial intelligence and machine learning engineering, encompassing advanced AI application development and operational deployment. The AI Engineer’s contributions will support ongoing advancements in enterprise digital transformation leveraging next-generation AI technologies.