AI Engineer (DEX Factory)

Responsibilities:
Ideate, design, prototype, and implement AI solutions that automate IT operations and enhance employee experience.
Translate operational pain points, incidents, requests, and repetitive engineering tasks into AI-enabled automation opportunities with measurable business value.
Build and maintain AI, ML, and generative AI components such as LLM-based assistants, RAG pipelines, orchestration workflows, and intelligent remediation capabilities.
Integrate AI solutions with enterprise platforms and data sources, including IT service management, endpoint management, and employee experience tooling.
Apply responsible AI, privacy, security, and governance principles throughout design, development, and deployment.
Use engineering best practices, including version control, peer review, testing, CI/CD, and operational observability.
Contribute to MLOps and LLMOps practices, including model evaluation, prompt quality, performance monitoring, drift awareness, safety controls, and cost management.
Collaborate with platform leads, architects, security teams, and business stakeholders to shape scalable and supportable solutions.
Document solutions clearly and support knowledge sharing across the team.
Drive continuous improvement through experimentation, analytics, and iterative delivery.
Requirements:
The ideal candidate combines hands-on AI engineering capability with a practical product mindset and a strong interest in improving IT operations and digital employee experience.
The role requires curiosity, sound judgment, and the ability to move from concept to production.
3-5 years of software engineering, automation engineering, or AI engineering experience, with evidence of delivering production solutions.
University degree in computer science, data science, engineering, or equivalent relevant experience.
Strong hands-on experience with Python and common AI or ML libraries and frameworks.
Practical experience building LLM-based applications, including retrieval-augmented generation, prompt design, tool calling, or agent-style workflows.
Working knowledge of cloud AI services such as Azure OpenAI, Azure AI Foundry, AWS Bedrock, or similar platforms.
Experience integrating with enterprise APIs, data sources, and automation platforms; familiarity with vector databases is beneficial.
Understanding of AI security, privacy, responsible AI practices, and relevant regulatory expectations, including EU AI Act principles.
Working knowledge of Azure DevOps or equivalent tooling for source control and CI/CD.
Strong analytical, documentation, and problem-solving skills.
Strong communication and collaboration skills with the ability to work independently when required.
Proficiency in written and spoken English.
German, Italian, or Spanish would be an advantage but are not essential.
Beneficial Experience:
Experience with agentic AI frameworks or orchestration patterns.
Knowledge of ServiceNow, Microsoft Intune, Nexthink, or Microsoft 365 and Copilot ecosystems.
Exposure to MLOps or LLMOps tools, evaluation frameworks, or model lifecycle management practices.
Data engineering or analytics skills such as SQL, data pipelines, or Power BI.
Relevant certifications such as Azure AI Engineer or ITIL Foundation.

Experience
10-14 yrs