AI / Prompt Developer – ML Engineer

Enterprise Solutions Inc.; Montreal (administrative region); On-site; CAD 110,000 - 150,000; Full time

Job summary

Enterprise Solutions Inc. seeks an AI Engineer specializing in GenAI, LLMOps and MLOps to design, develop and deploy scalable, production‑grade ML and generative AI solutions in a Montreal environment.

The role focuses on end‑to‑end model lifecycle management, advanced LLM applications, and building fast, secure APIs with Python, FastAPI and containerized deployments, collaborating with data scientists and engineers to deliver enterprise‑grade AI capabilities.

Qualifications

• Experience designing GenAI and MLOps in production environments.
• Proficient in Python and SQL.
• Experience deploying scalable APIs with Docker/Kubernetes.
• Familiar with vector databases and data pipelines.

Responsibilities

• Design, develop and deploy production-grade ML and Generative AI solutions.
• Manage full ML model lifecycle from training to retraining.
• Build scalable enterprise APIs using FastAPI.
• Collaborate with cross-functional teams to productionize AI solutions.
• Stay updated on GenAI, LLMOps and MLOps best practices.
• Troubleshoot and optimize AI workflows in production.
• Document AI system architecture and deployment processes.

Skills

GenAI - LLMOps

Python

SQL

MLOps

Docker

Kubernetes

FastAPI

LangChain

Tools

PyTorch

TensorFlow

Spark

Iceberg

Pgvector

Chroma

OpenShift

Job description

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

Responsibilities

• Design develop and deploy productiongrade 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 RetrievalAugmented Generation RAG pipelines
• Automate complex workflows and enhance user experiences through AIdriven solutions
• Collaborate with crossfunctional teams to transition AI models from prototypes to scalable secure and highperformance 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

Responsibilities - Roles and Responsibilities

• Design and implement endtoend 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

Required Skills

• Mandatory Skills
• GenAI - LLMOps
• Python

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.