AI Engineer (GenAI / LLM)
Role summary
We are seeking an experienced AI Engineer specializing in Generative AI and Large Language Models (LLMs) to join our team in Mississauga, Canada. This hybrid role involves designing, building, and deploying enterprise-grade AI solutions, including RAG pipelines, prompt engineering, and agent-based systems. The ideal candidate will have a strong background in Python, ML, Data Science, NLP, and experience with LLMs like OpenAI and Gemini, vector databases, and MLOps practices. You will integrate AI capabilities into enterprise systems and ensure model safety and performance.
AI Engineer (GenAI / LLM)
Location: Mississauga, Canada (Hybrid)
About the Role
We are looking for experienced Service AI Engineers with strong expertise in Generative AI and Large Language Models (LLMs) to design, build, and deploy enterprise-grade AI solutions.
If you have a solid background in Python + LLMs (or Java + LLMs with willingness to work in Python), this is a great opportunity to work on cutting-edge AI initiatives.
Key Responsibilities
Design, develop, and deploy LLM-powered applications in production environments
Build and optimize Retrieval-Augmented Generation (RAG) pipelines
Implement advanced prompt engineering, tuning, and reusable templates
Develop agent-based AI solutions using modern frameworks
Integrate AI capabilities with enterprise systems via APIs and orchestration tools
Work with vector databases for efficient semantic search and retrieval
Handle and process large-scale unstructured datasets
Ensure AI model safety, performance, and governance (Guardrails)
Collaborate with cross-functional teams to deliver scalable AI solutions
Required Skills & Experience
Core Requirements
9–10 years of experience in Application Development / Systems Analysis
Strong foundation in:
Machine Learning
Data Science & Statistics
NLP & Neural Networks
Large Language Models (LLMs)
Generative AI Expertise
Hands-on experience with LLMs such as:
OpenAI, Gemini, Claude, Mistral, Llama
Strong experience in:
RAG pipelines (must-have)
Prompt Engineering & Tuning
LLM application development & deployment
Experience with platforms like Vertex AI, Hugging Face
Programming & Tools
Strong proficiency in Python (mandatory)
Experience with libraries/tools:
Pandas, NumPy, scikit-learn
PyTorch / TensorFlow
Transformers, FastAPI
LangChain, LlamaIndex
Data & Integration
Experience with vector databases:
Pinecone, PGVector, Mongo Atlas, Neo4j
Knowledge of API integration and knowledge graphs
Experience working with large-scale unstructured data
Deployment & MLOps
Hands-on experience deploying AI/ML models to production
Strong understanding of MLOps and model evaluation
Experience with CI/CD tools:
Jenkins, GitLab CI, Azure DevOps, ArgoCD
Cloud & Containers
Experience with Kubernetes / OpenShift
Exposure to cloud-native architecture