Senior AI Engineer (GenAI / LLM)
Role summary
We are seeking a Senior AI Engineer with a focus on Generative AI and Large Language Models (LLMs) to join our team in Mississauga. The role requires 6-10 years of experience in application development or systems analysis, with a strong foundation in ML, Data Science, and AI. Key responsibilities include hands-on experience with LLMs (e.g., OpenAI, Gemini), RAG pipelines, deploying LLM applications on platforms like Vertex AI and Hugging Face, and expertise in prompt engineering. Proficiency in Python, handling large-scale unstructured data, MLOps, and cloud-native technologies like Kubernetes is essential. This hybrid role emphasizes building and deploying AI solutions at scale.
Senior AI Engineer (GenAI / LLM)
Location: Mississauga, Canada (Hybrid)
We are looking for a highly skilled Senior AI Developer with strong expertise in Generative AI and Large Language Models (LLMs) to join our growing team. If you are passionate about building cutting-edge AI solutions and deploying them at scale, this opportunity is for you!
Key Requirements
6–10 years of experience in application development or systems analysis
Strong foundation in Machine Learning, Data Science, Statistics, and AI fundamentals
Hands-on experience in NLP, Neural Networks, and LLMs
Generative AI & LLM Expertise
Experience with LLMs like OpenAI, Google Gemini, Anthropic Claude, Mistral, LLaMA, and other open-source models
Deep expertise in Retrieval-Augmented Generation (RAG) pipelines (must-have)
Strong experience in building and deploying LLM-based applications using platforms like Vertex AI, Hugging Face
Expertise in prompt engineering, prompt tuning, and reusable prompt frameworks
Hands-on experience with agentic frameworks and GenAI guardrails
Programming & Data Engineering
Strong proficiency in Python (preferred) or Java (with willingness to work on Python)
Experience with libraries/tools: Pandas, NumPy, scikit-learn, PyTorch, TensorFlow, Transformers, FastAPI, LangChain, LlamaIndex
Experience with vector databases: PGVector, Pinecone, MongoDB Atlas, Neo4j
Strong experience handling large-scale unstructured data
Deployment & MLOps
Proven experience deploying GenAI solutions to production
Strong knowledge of MLOps, model evaluation, and deployment pipelines
Experience with CI/CD tools: Jenkins, GitLab CI, Azure DevOps, ArgoCD
Cloud & Containerization
Hands-on experience with Kubernetes / OpenShift
Experience in building and managing cloud-native applications
Soft Skills
Strong problem-solving and analytical skills
Ability to work independently and collaborate with cross-functional teams
Comfortable working in fast-paced, ambiguous environments