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AI Engineer

Job in San Mateo, San Mateo County, California, 94403, USA
Listing for: Rootshell Inc
Full Time position
Listed on 2026-08-20
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), Machine Learning/ ML Engineer, Backend Developer, Cloud Engineer - Software
Job Description & How to Apply Below

AI Engineer

Rootshell Enterprise Technologies Inc. is a recognized provider of professional IT Consulting services in the US. We are actively seeking an AI Engineer for one of our clients.

Job Summary:

We are looking for an AI Engineer to design, develop, deploy, and maintain AI-powered applications and machine learning solutions. The ideal candidate should have strong programming skills, experience with machine learning and generative AI, and the ability to integrate AI models into scalable production systems.

Key Responsibilities
  • Design and develop AI/ML solutions for business requirements.
  • Build and deploy Generative AI and LLM-based applications.
  • Develop RAG (Retrieval-Augmented Generation) pipelines using embeddings and vector databases.
  • Integrate AI models through APIs and cloud services.
  • Develop AI agents and tool-calling workflows.
  • Train, fine-tune, evaluate, and optimize machine learning models when required.
  • Work with data scientists, software engineers, and product teams.
  • Build APIs and backend services for AI applications.
  • Implement model evaluation, monitoring, security, and performance optimization.
  • Deploy AI applications using cloud platforms and containerization technologies.
  • Stay current with emerging AI/ML technologies and best practices.
Required Skills
  • Strong Python programming skills.
  • Understanding of machine learning and deep learning concepts.
  • Experience with LLMs, Generative AI, prompt engineering, and RAG.
  • Familiarity with frameworks such as PyTorch, Tensor Flow, Hugging Face, Lang Chain, or Llama Index.
  • Knowledge of REST APIs and backend development.
  • Experience with SQL and databases.
  • Familiarity with vector databases and embedding models.
  • Knowledge of Docker and cloud platforms such as AWS, Azure, or GCP.
  • Understanding of Git, CI/CD, testing, and production deployment.
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