Senior Lead DEX Factory AI Engineer

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:
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
8-12 yrs