
AI Developer
Calliere · Toronto, Ontario, Canada
Weak hiring record · median 93 days open
All reasons
- Open 63 days
- 86% of this employer's openings are over 60 days old
In its favour
- Still listed on the employer's own board
Location
Toronto or Montreal.
A leading North American financial institution is seeking an AI Developer to build software solutions that incorporate artificial intelligence and machine learning capabilities. The successful candidate will work with product, data, platform, and engineering teams to develop secure, scalable, and production-ready AI applications.
Responsibilities
- Design and develop AI-enabled applications, services, and APIs.
- Integrate machine-learning models and generative AI capabilities into enterprise systems.
- Build data-processing, retrieval, evaluation, and model-integration workflows.
- Develop prompts, model interactions, and application logic for AI use cases.
- Implement automated testing, monitoring, logging, and performance measurement.
- Collaborate with data scientists, platform engineers, business analysts, and product owners.
- Apply security, privacy, responsible-AI, and governance practices.
- Troubleshoot application, integration, and model-related issues.
- Document technical designs, interfaces, and operational processes.
- Participate in code reviews, Agile ceremonies, and continuous improvement.
Qualifications
- Experience in software development with Python and/or another modern programming language.
- Experience developing APIs, services, and production applications.
- Familiarity with machine learning, natural-language processing, or generative AI.
- Experience with cloud platforms, databases, version control, and CI/CD.
- Understanding of software testing, security, and application architecture.
- Strong analytical and problem-solving skills.
Preferred Skills
- Experience with large language models, prompt engineering, RAG, embeddings, or vector databases.
- Familiarity with frameworks such as LangChain, LlamaIndex, Semantic Kernel, or comparable tools.
- Experience with MLflow, model evaluation, or model-serving platforms.
- Knowledge of financial services, data privacy, and regulated environments.
Skills
- Machine Learning
- Generative AI
- Python
- LLM
- Prompt Engineering
- Retrieval-Augmented Generation
- Embeddings
- Vector Databases
- LangChain
- LlamaIndex
- Semantic Kernel
- MLflow
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