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5 часов назад

Lead AI Engineer (GenAI)

Формат работы
remote
Тип работы
fulltime
Грейд
lead
Английский
b2
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

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TL;DR

Lead AI Engineer (GenAI): Designing and implementing end-to-end Generative AI applications, specifically document intelligence and RAG pipelines, with an accent on scalability, latency, and cost optimization. Focus on building agentic workflows, fine-tuning LLMs, and productionizing AI services using MLOps best practices.

Location: Remote

Company

hirify.global is a technical consultancy that treats AI as a software engineering discipline to build robust, scalable production services for a diverse range of clients.

What you will do

  • Architect and build GenAI applications using Python, LangChain, and LlamaIndex on Google Cloud.
  • Develop advanced RAG pipelines and Semantic Search systems using Google Cloud Vector Search or Pinecone.
  • Lead LLM and Embedding fine-tuning to improve domain-specific performance.
  • Build and manage agentic workflows to automate complex multi-step reasoning tasks.
  • Collaborate with customers to translate business needs into high-performance AI architectures.
  • Apply MLOps best practices to ensure models are served efficiently and continuously improved.

Requirements

  • 8+ years of experience in AI/ML.
  • Proven track record of deploying GenAI products to a production environment.
  • Mastery of Python and shell scripting.
  • Deep knowledge of Google Gemini, GPT-4, or LLaMA, including Prompt Engineering and Fine-tuning.
  • Expertise in Vector Databases (Vertex AI Vector Search, pgvector, etc.) and Semantic Search.
  • Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field.

Nice to have

  • Experience with Classic Machine Learning (neural nets, training, tuning).
  • Knowledge of Data Engineering and SQL.

Culture & Benefits

  • Culture of ownership where you see projects through from concept to deployment.
  • Environment that encourages lifelong learning to stay ahead of the fast-changing AI landscape.
  • Consultative atmosphere focusing on translating technical complexity into business value.
  • Strong commitment to responsible AI development and data privacy.

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