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Artificial Intelligence Engineer

@ Enterprise Solutions Inc.

Toronto, Ontario

Contract
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SIGNALS

Responsibilities:

  • Design and implement end to end AIML solutions incorporating GenAI and LLMOps best practices
  • Develop and maintain scalable secure APIs for AI model deployment
  • Manage full ML model lifecycle including training validation deployment monitoring and retraining
  • Collaborate with data scientists engineers and product teams to integrate AI solutions into enterprise applications
  • Optimize AI workflows to ensure high performance and reliability in production environments
  • Stay updated with the latest advancements in Generative AI LLMOps and MLOps to continuously improve solutions

Requirements summary:

  • Design develop and deploy production grade Machine Learning and Generative AI solutions Build intelligent systems including predictive ML models covering complete model lifecycle…
Source and dates

Source type not verified · apify-linkedin

Employer posting date
2026-11-09
First seen by our source
2026-11-10
Source record updated
2026-11-10

These dates describe the source record, not a live verification that the employer is still hiring. Check the original posting.

Enterprise Solutions Inc.

FieldValue
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Job description

Job Title - AI Developer

Mandatory Skills: GenAI - LLMOps, Python

Type - Fulltime

Location - Onsite - Toronto , ON

Mandatory Certifications

Databricks Certified Generative AI Engineer Associate

Google Professional Machine Learning Engineer

NVIDIA Certified Professional - Agentic AI (NCP-AAI)

AWS Certified AI Practitioner

Summary:

Seeking an AI Engineer skilled in GenAI LLMOps and MLOps to design develop and deploy scalable production grade machine learning and generative AI solutions

Job Description:

Design develop and deploy production grade Machine Learning and Generative AI solutions Build intelligent systems including predictive ML models covering complete model lifecycle management Develop advanced applied Large Language Model LLM applications and Retrieval Augmented Generation RAG pipelines Automate complex workflows and enhance user experiences through AIdriven solutions Collaborate with cross functional teams to transition AI models from prototypes to scalable secure and high performance enterprise APIs Utilize expertise in Python programming and SQL for solution development Implement Generative AI techniques including LLMs LangChain LangGraphs Claude Gemini prompt engineering and LLMOps Apply Machine Learning and Deep Learning frameworks such as PyTorch TensorFlow ScikitLearn and XGBoost Work with vector databases like Pgvector and Chroma for efficient data retrieval Leverage distributed processing tools including Apache Spark and Apache Iceberg Employ MLOps practices for deployment using Docker KubernetesOpenShift and FastAPI Build highperformance scalable APIs with Python FastAPI to expose AI capabilities required for solutions

Roles and Responsibilities:

  • Design and implement end to end AIML solutions incorporating GenAI and LLMOps best practices
  • Develop and maintain scalable secure APIs for AI model deployment
  • Manage full ML model lifecycle including training validation deployment monitoring and retraining
  • Collaborate with data scientists engineers and product teams to integrate AI solutions into enterprise applications
  • Optimize AI workflows to ensure high performance and reliability in production environments
  • Stay updated with the latest advancements in Generative AI LLMOps and MLOps to continuously improve solutions
  • Troubleshoot and resolve issues related to AI model deployment and production systems
  • Document AI system architecture deployment processes and best practices

We are committed to fostering an inclusive workplace. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, or any other characteristic protected by applicable law.

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