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Staff Engineer - AI (M/F)

airliquidehr · Paris

Nouveau
Senior 🇬🇧 English
AI architecture Knowledge graphs Semantic data Cloud SDLC

Description du poste

About the role

Air Liquide's AI Governance & Architecture team defines long-term technical strategies and governance frameworks so that AI solutions are robust, scalable and compliant. As a Staff Engineer, you will lead technical strategies and architecture, mentor other engineers and accelerate AI adoption in key business value streams such as Customer Care, Industrial/Operations and Global Business Services. The position is based in Paris.

Key responsibilities

  • Analyze complex technical challenges, find root causes and develop solutions aligned with project and business goals
  • Anticipate AI trends and turn them into technical roadmaps, championing disruptive technologies and frameworks
  • Lead cross-functional teams in designing and implementing technical solutions and act as a subject matter expert
  • Contribute to a technical committee (Local TADA) and share best practices and knowledge across and beyond teams
  • Define and deploy long-term technical strategies aligned with Air Liquide's Data & AI strategy, assessing the feasibility of proposed initiatives
  • Lead Data & Knowledge Management strategy and governance, including policies, guidelines and Architecture Decision Records (ADRs)
  • Advance AI algorithms and computational technologies, and manage technical risks, technical debt and system vulnerabilities

Required profile

  • Minimum 8 years of experience in system and solution design and architecture
  • Ability to develop and communicate a technical influence strategy
  • Demonstrated mentoring and coaching abilities
  • Strong analytical, problem-solving and strategic thinking skills
  • Prior knowledge of some Air Liquide business domains is a plus

Required skills

  • Proficiency in the software development life cycle (SDLC)
  • Scalable, robust and high-performance architecture design
  • Data and knowledge management frameworks (structured, unstructured, semantic data, knowledge graphs)
  • Architectural governance, policy definition and ADR practices
  • Production-grade AI architecture deployment and maintenance
  • Design of computational frameworks and advanced AI algorithms
  • Broad knowledge of cloud and integration technologies

Questions fréquentes

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Source : ats:workday

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airliquidehr

Paris