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Uni Systems

European systems integration and ICT services

AI Enablement Lead

Engineering LeadershipConfirmed live in the last 24 hours
Full-timeAthens, GreeceNo salary listed

About the Job

Requirements

  • A university degree in Computer Science, Computer Engineering, Software Engineering, or a related field.
  • 10–15 years of experience in IT, including at least 5 years in a senior delivery role as an Engineer, Solution Architect, or Technical Lead in a services organisation.
  • Daily hands-on use of AI coding and knowledge tools, with concrete examples of workflows built for oneself or a team.
  • Sound understanding of the full software development life cycle and where AI does and does not help in each phase.
  • Working knowledge of continuous integration and continuous delivery, containerisation, and cloud-native architectures.
  • Working understanding of AI solution design and evaluation, including prompting patterns, retrieval-augmented generation, model selection, and evaluation, sufficient to guide designs and assess feasibility.
  • Ability to explain and teach techniques in a tangible way, including to sceptical colleagues.
  • Ability to turn hands-on experience into actionable advice and structured input for internal decisions and clients, and to present to technical and non-technical audiences.
  • Excellent command of English, verbally and in writing.

Responsibilities

  • Deliver as a senior member of the client engagement team, working hands-on across software development life cycle phases relevant to the employee’s background.
  • Apply AI tools to real delivery work and build repeatable, production-ready workflows, reusable prompts, and software development life cycle-aligned templates; document what works and what does not so it can transfer to other engagements.
  • Establish with the client and security and legal functions what may be processed by hosted AI services under contractual, data-protection, and intellectual-property constraints; design compliant workflows and use the in-house private AI environment when data cannot leave organisational control.
  • Keep humans accountable for outcomes by ensuring AI output remains an input to engineering judgement rather than a final decision.
  • Build the client relationship and serve as a point of reference for AI questions arising in the engagement.
  • Act as an internal consultant to delivery teams by understanding their work, advising on realistic AI uses in context, and providing structured recommendations that state trade-offs, effort, and risks.
  • Run hands-on sessions, share working examples, and connect colleagues across architecture, business analysis, and engineering who already use AI tools in projects.
  • Establish the department’s AI adoption baseline, including tools used, users, use cases, and effects, to enable measurement of later progress.
  • Support the AI Governance Office in operationalising responsible-AI practices in the Engineering Department, including transparency, human oversight, traceability, and appropriate use of AI output in deliverables; help colleagues meet the AI literacy duty under Article 4 of the EU AI Act.
  • Track and report department AI tooling spend, flag anomalies, and contribute to business cases for new tooling; budget ownership remains with Finance and the Head of the Engineering Department.
  • Contribute with Practice Managers and delivery squads to the Engineering Department AI adoption roadmap and advise on the transition plan for introducing AI tools and methods into delivery practice, including sequencing, pilots, rollout, training needs, and replacement or retirement of existing tools.
  • Guide AI-integrated solution designs and reference architectures, and steer proofs of concept and pilots toward production use.
  • Design role-based learning paths and an upskilling roadmap across engineering roles, mentor colleagues, and build community.
  • Support the Bidding team with AI capability statements, technical narratives, and differentiators for tenders and proposals; present at client workshops and innovation events.
  • Contribute to AI cost governance through cost-centre allocation, quotas and alerts, and optimisation using model selection, prompt efficiency, caching, and appropriately sized compute.

Desired Qualifications

  • Delivery experience in regulated environments or with EU institutions and agencies.
  • Exposure to tenders, proposals, or pre-sales work.
  • Awareness of cloud cost management and usage-based pricing models.
  • Familiarity with the EU AI Act, the General Data Protection Regulation, data governance, or ISO/IEC 42001.
  • Exposure to running large language models in an organisation-controlled environment, including private or sovereign deployment and secure enterprise integration.
  • Additional EU languages.

About the Company

Uni Systems

European systems integration and ICT services

Uni Systems provides ICT services with a focus on systems integration for enterprises. It designs and implements technology solutions by coordinating hardware, software, and services to meet client goals, often spanning consulting, deployment, and managed support across end-to-end IT projects. Originating as one of Greece’s first IT firms, it built a long track record in establishing computer systems at universities and expanded through acquisitions and cross-border operations. Today, part of the Quest Group, Uni Systems differentiates itself through its extensive European footprint, history of strategic acquisitions (e.g., Intelli Solutions) and minority stake in Compellio, and its ability to deliver large-scale IT programmes across more than 20 countries. The company’s goal is to be a leading ICT corporation in Europe, helping organizations modernize and connect their technology ecosystems through integrated solutions and services.

Company size
501-1,000
Company stage
Not listed
Total funding
Not listed
Headquarters
Athens, Greece
Founded
1964

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