Job Description
Ovii's Interpretation of the Role
The AI Engineer will design, build, and deploy generative‑AI applications using large language models, RAG pipelines, and prompt engineering. The role requires deep Python expertise, MLOps, and cloud‑native deployment on Kubernetes/OpenShift environments.
Role Snapshot
- Generative AI application development
- LLM model tuning & deployment
- RAG pipeline implementation
- Prompt engineering & guardrails
- MLOps & CI/CD automation
- Cloud‑native container orchestration
Must-Have Requirements
- Python programming
- RAG pipeline development
- Prompt engineering
- Vector database usage
- MLOps deployment
- CI/CD automation
- Kubernetes/OpenShift orchestration
- Cloud platform experience (Vertex AI, Hugging Face)
- Apps development or systems analysis
- Generative AI and LLM expertise
- must be authorized to work in the U.S. (E‑Verify)
Nice-to-Have Signals
- Experience with Google Gemini, OpenAI, Anthropic Claude, Mistral, Llama
- Guardrails and safety assessment
- Agentic framework implementation
- Specific LLM platforms (Google Gemini, OpenAI, Anthropic Claude, Mistral, Llama)
Work Setup
- Location: Mississauga, Canada
- Work mode: ONSITE
- Employment type: Contract
Eligibility Gates
- Work authorization: must be authorized to work in the U.S.
- Visa sponsorship: no
Not Specified in JD
- Salary range
- Visa sponsorship
- Remote eligibility
- Education requirement
- Certifications
- Relocation
- Notice period
- Travel
- Security clearance
- Coding test
What You'll Likely Work On
- Build and fine‑tune LLM‑based applications across multiple domains
- Design and implement advanced RAG pipelines and prompt templates
- Integrate generative AI services with enterprise APIs, knowledge graphs, and orchestration tools
- Create and maintain robust MLOps deployment pipelines with automated testing and monitoring
- Develop CI/CD workflows and containerized solutions for scalable production
- Collaborate with cross‑functional teams to ensure safety, performance, and compliance of AI features
Good Fit If You Have
- Enjoys solving ambiguous problems independently
- Thrives in collaborative, cross‑functional environments
- Passionate about staying current with emerging GenAI models and techniques
Skills
- Python & ML libraries (Pandas, NumPy, scikit‑learn, PyTorch, TensorFlow, Transformers)
- Retrieval‑Augmented Generation (RAG)
- Prompt engineering & tuning
- Vector databases (PG Vector, Pinecone, MongoDB Atlas, Neo4j)
- MLOps pipelines for GenAI models
- CI/CD tools (Jenkins, GitLab CI, Azure DevOps, ArgoCD)
- Kubernetes / OpenShift orchestration
- Cloud platforms (Vertex AI, Hugging Face)