AI Engineer
- Toronto, ON, Canada
Contract
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Job details
- Job type
- Contract
- Apply by
- Experience
- 3–5+ years of AI development experience, including at least 2 years building production AI/ML or Agentic AI solutions.
- Posting language
- English
- Posted
Original job description
Our client, a leading financial institution in Toronto, is seeking an AI Engineer to support a large enterprise AI transformation program. The successful candidates will design, build, and deploy production-grade AI, Machine Learning, and Agentic AI solutions that address complex business challenges in an enterprise environment.
Responsibilities
- Design and implement production-grade AI and Agentic AI solutions.
- Build AI agents, agentic workflows, and Retrieval Augmented Generation (RAG) pipelines.
- Develop AI/ML pipelines using LLMs and SLMs.
- Implement MLOps, LLMOps, CI/CD, and cloud deployment best practices.
- Build AI governance, monitoring, observability, and evaluation frameworks.
- Contribute to AI standards, accelerators, and delivery best practices.
Required Qualifications
- Degree in Computer Science, Software Engineering, Data Science, or a related field.
- 3–5+ years of AI development experience, including at least 2 years building production AI/ML or Agentic AI solutions.
- Strong Python development skills.
- Experience building and deploying AI agents and AI/ML solutions.
- Experience with Docker, Kubernetes, CI/CD, and version control.
- Experience with API integration and development.
- Consulting or professional services experience preferred.
Technical Environment
- Python
- LangGraph
- CrewAI
- LLMs / SLMs
- Retrieval Augmented Generation (RAG)
- MLOps / LLMOps
- Docker
- Kubernetes
- CI/CD
- AI Gateways (MCP, A2A)
- API Development
- Cloud AI Platforms
More about this job
Responsibilities
The AI Engineer at Myticas Consulting will design and deploy production AI and agentic AI solutions for a bank. The work includes building AI agents, retrieval pipelines, monitoring and governance frameworks.
Requirements
Candidates need a computer science, software engineering or data science degree, strong Python skills, and hands-on experience deploying AI agents and ML systems. Docker, Kubernetes, CI/CD and API development experience are also required.
Skills
- Python
- LangGraph
- CrewAI
- Large language models
- Small language models
- Retrieval Augmented Generation
- AI agents
- Agentic workflows
- MLOps
- LLMOps
- Docker
- Kubernetes
- CI/CD
- Version control
- API integration
- API development
- Model Context Protocol (MCP)
- Agent-to-Agent (A2A)
- AI governance
- Model monitoring
- Observability
- Model evaluation
- Cloud AI platforms
- Machine learning pipelines
- Consulting
Categories
- Technology
- Software
- Data & Analytics
- Finance & Accounting
Keywords
- AI Engineer
- Agentic AI
- Machine Learning
- Python
- LangGraph
- CrewAI
- LLM
- SLM
- Retrieval Augmented Generation
- RAG
- MLOps
- LLMOps
- Docker
- Kubernetes
- CI/CD
- MCP
- A2A
- AI Gateway
- API development
- Cloud AI platform
Seniority
Mid level
Tools
- Python
- LangGraph
- CrewAI
- Docker
- Kubernetes
Languages
- English
Fields of study
- Computer Science
- Software Engineering
- Data Science