AI Engineer

Compunnel Inc.; Toronto; On-site; CAD 90,000 - 120,000; Full time

Job summary

Compunnel, Inc. is looking for a skilled AI Engineer in Toronto, Canada. This role requires expertise in advanced Python programming and AI/ML frameworks to build innovative AI solutions. The ideal candidate will have 5+ years of experience, particularly in investment banking or capital markets, and knowledge of large language models (LLMs) and generative AI technologies. Responsibilities include designing AI models, optimizing performance, and integrating solutions into enterprise systems.

Qualifications

• 5+ years of experience in advanced Python programming.
• Strong expertise in prompt engineering and generative AI applications.
• Hands-on experience with large language models (LLMs).

Responsibilities

• Design, develop, test, and deploy advanced AI/ML models and algorithms using Python.
• Optimize prompt engineering techniques to improve AI model performance.
• Build AI-driven solutions into enterprise systems.

Skills

Advanced Python programming

AI/ML frameworks

Generative AI technologies

Large language models (LLMs)

Prompt engineering

Retrieval-augmented generation (RAG)

Vector databases

AI agentic frameworks

Collaboration skills

Problem-solving skills

Education

Bachelor’s or Master’s degree in Computer Science, AI, or related field

Tools

TensorFlow

PyTorch

Hugging Face

AWS

Azure

Google Cloud

Job description

We are seeking a skilled AI Engineer with expertise in advanced Python programming, AI/ML frameworks, and modern generative AI technologies. The ideal candidate will have experience working with large language models (LLMs), prompt engineering, retrieval-augmented generation (RAG), vector databases, and AI agentic frameworks to build scalable and innovative AI-driven solutions.

Key Responsibilities

• Design, develop, test, and deploy advanced AI/ML models and algorithms using Python.
• Develop and optimize prompt engineering techniques to improve AI model performance and response quality.
• Build and integrate AI-driven solutions into enterprise systems and business workflows.
• Utilize AI agentic frameworks to develop intelligent and autonomous AI applications.
• Work with large language models (LLMs) to create applications capable of generating and understanding natural language.
• Implement retrieval-augmented generation (RAG) strategies to improve contextual relevance and response accuracy.
• Manage and optimize vector databases for efficient data storage, indexing, and retrieval.
• Collaborate with cross-functional teams including engineering, product, and business stakeholders.
• Conduct research on emerging AI/ML technologies and evaluate new tools and methodologies.
• Document AI models, workflows, technical processes, and implementation strategies.
• Ensure scalability, reliability, and performance of AI applications and services.

Required Qualifications

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
• 5+ years of experience in advanced Python programming with strong knowledge of data structures and algorithms.
• Experience working within Investment Banking or Capital Markets environments.
• Strong expertise in prompt engineering and generative AI applications.
• Familiarity with AI agentic frameworks and intelligent automation solutions.
• Hands‑on experience working with large language models (LLMs).
• Knowledge of retrieval‑augmented generation (RAG) techniques and vector database technologies.
• Strong analytical, troubleshooting, and problem‑solving skills.
• Ability to communicate technical concepts effectively to both technical and non‑technical stakeholders.
• Experience working collaboratively within cross‑functional teams.

Preferred Qualifications

• Experience with AI/ML frameworks and libraries such as TensorFlow, PyTorch, or Hugging Face.
• Familiarity with cloud platforms including AWS, Azure, or Google Cloud and their AI/ML services.
• Knowledge of data preprocessing, data engineering, and data pipeline practices.