I
Inetum
AI Engineer

GenAI Engineer

On-siteSeniorAI Engineerposted 13mo ago
✦Role summaryAI-generated

This role demands a hands-on leader capable of architecting and deploying production-grade generative AI systems while bridging technical execution with business strategy. The ideal candidate thrives at the intersection of cutting-edge AI innovation and cloud-native scalability, driving impactful solutions in a collaborative environment.

Skills required

About this role

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.

Qualifications

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.

Additional Information

  • 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.
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