AI Engineer - Banking Domain

Job summary

Design and deploy production-grade machine learning and generative AI solutions for banking use cases such as fraud detection and credit risk. Implement MLOps best practices and ensure compliance with financial regulatory guidelines and governance frameworks.

Job details

Engagement Contract — 12 months, renewable Domain Banking & Financial Services Locations Toronto, ON | Montreal, QC | Vancouver, BC | Calgary, AB Work Model Hybrid Start Immediate ABOUT THE ROLE We are looking for an experienced AI Engineer to design and deliver production-grade machine learning and generative AI solutions within a major Canadian bank. You will work across fraud detection, credit risk, regulatory compliance, and customer analytics, partnering with data, engineering, and compliance teams to bring AI from prototype to production. KEY RESPONSIBILITIES Build and deploy ML and GenAI solutions for banking use cases (fraud, AML, credit scoring, customer analytics). Design LLM-based applications including RAG pipelines and document intelligence for internal workflows. Implement MLOps best practices: model versioning, CI/CD, monitoring, and drift detection. Ensure compliance with OSFI model risk guidelines, PIPEDA/CPPA, and internal governance frameworks. Communicate model performance and business impact to technical and non-technical stakeholders. MUST-HAVE 7+ years in AI/ML engineering, with 3+ years in banking or financial services. Advanced Python skills: PyTorch/TensorFlow, Scikit-learn, Pandas. Hands-on MLOps experience: MLflow, Kubeflow, Azure ML, or SageMaker. LLM/GenAI development: OpenAI, Azure OpenAI, LangChain, RAG architectures. Cloud proficiency: Azure (preferred), AWS, or GCP. Knowledge of OSFI E-23 model governance, PIPEDA, and explainable AI for audits. Experience with SQL and distributed data platforms (Spark, Databricks, or Snowflake). GOOD TO HAVE Azure AI-102, AWS ML Specialty, or Google Professional ML Engineer certification. Exposure to IFRS 9, Basel III, or Open Banking frameworks. Experience with real-time ML inference (Kafka, Flink). Bilingual English/French (asset for Montreal). FRM or CFA designation as a complement to technical skills. HOW TO APPLY Submit your resume, preferred location, and available start date. Canadian work authorization required.

What you’ll do

Design and deploy production-grade machine learning and generative AI solutions for banking use cases such as fraud detection and credit risk. Implement MLOps best practices and ensure compliance with financial regulatory guidelines and governance frameworks.

Requirements

Requires over 7 years of AI/ML engineering experience, including at least 3 years within the banking or financial services sector. Proficiency in Python, cloud platforms (Azure preferred), and LLM development is essential.

Listed skills

• Microsoft Azure · Preferred
• Production · Preferred
• Technical · Preferred
• CI/CD · Preferred
• Data analysis · Preferred
• Compliance · Preferred
• Machine learning · Preferred
• Development · Preferred
• Amazon Web Services · Preferred
• Customer · Preferred
• Python · Preferred
• Bilingual communication · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Python
• PyTorch
• TensorFlow
• Scikit-learn
• Pandas
• MLOps
• MLflow
• Kubeflow
• Azure ML
• SageMaker
• LLM
• LangChain
• RAG
• Azure
• SQL
• Spark

Job areas

• Technology
• Data & Analytics
• Finance & Accounting
• Software
• Engineering

More jobs from Jay Analytix Inc