Auto-apply is a Pro feature

Let Findyet apply to this job for you:

  • Your CV is tailored to this posting.
  • The application form's questions are answered from your profile.
  • You review everything and approve before anything is sent.
  • Findyet submits the application and adds it to your tracker.

Available on Greenhouse postings today, up to 3 applications a day on Pro.

The first 100 verified accounts get Pro free for 90 days.

See plans

Inetum

GenAI Engineer

Posted Updated
Discussion

We are seeking a talented and experienced Generative AI Engineer to lead the development and deployment of cutting-edge AI solutions. This role will focus on building scalable applications using Generative AI technologies, integrated within our cloud infrastructure, and aligned with strategic business needs.

Key Responsibilities:

  • Independently develop GenAI-based applications tailored to product requirements.
  • Implement scalable and high-performance AI solutions.
  • Integrate AI applications with existing internal systems.
  • Lead and collaborate with cross-functional teams to drive AI strategy and execution.

Required Qualifications:

  • Proven experience in Machine Learning, Generative AI, or related fields.
  • Strong leadership and communication skills.
  • Advanced knowledge of integrating Generative AI into cloud infrastructures.
  • Ability to design and implement AI strategies at scale.

Programming & AI Frameworks:

  • Proficiency in Python and relevant ML libraries.
  • Experience with LangChain, Semantic Kernel, Hugging Face Transformers.
  • Familiarity with Apache Lucene/Solr/LuceneSearch.

Generative AI & LLMs:

  • Experience building applications with LLMs on Microsoft Azure (GPT-4o, o3).
  • Use of Azure OpenAI models (GPT-3.5 Turbo, GPT-4).
  • Experience with Azure AI Services (genai-ltst, gpt-4o-mini-realtime-preview).
  • OCR and Embedding tools (Azure Document Intelligence, text-embedding-s-small/b-large).

Cloud & DevOps:

  • Strong experience with Microsoft Azure Cloud platform.
  • CI/CD pipeline development using GitHub Actions.
  • Containerization using Docker; Azure Container Registry is a plus.
  • Infrastructure as Code using Terraform.
  • Experience with Azure Key Vault and GitHub Actions Secrets.

  • Hands-on experience with Azure Cognitive Search and Semantic Kernel.
  • Experience deploying and maintaining scalable AI pipelines.
  • Strong understanding of feedback loops and evaluation metrics in AI systems.

Skills

What Senior AI Engineering jobs ask for — and how much of it you have →
Apply

See also

AI Engineering jobs by country — openings, pay and top skills →

Tailor your CV for this role?

We couldn't check your fit for this role — add a CV to your profile to see it next time.