Full Stack Developer - AI

NOTE

Hybrid work model, 3 days/week in Toronto, Ontario office.

1-Year Contract, 8 hours/day, 40 hours/week (possibility of extension)

5+ years Full Stack Developer, AI/ML, Python, C#, REST API, Azure, Jenkins, Snowflake, LLM, GPT, Claude, Llama, Agentic AI, advanced text to SQL, LoRA Adapter, RAG pipelines

Investment, Bank

• With supervision and code/design reviews by senior staff, responsible for the timely completion of high-quality, well-designed systems that make appropriate use of technology.
• Responsible for the completion of an acceptable volume of work and for the communication of the status of personal work plans and tasks required to design, develop, and test assigned portions of projects.
• Responsible for maintaining currency in technological trends and directions, continually upgrading personal technical and IT-related skills through research, education and self-motivated technology experimentation.
• Participate in new technology investigation and make recommendations for new technology adoption where appropriate
• Computer Science, Artificial Intelligence, Data Science, or Engineering degree. Master’s degree is preferred
• 5+ years software design/development experience with sufficient knowledge with AI/ML or strong hands‑on knowledge and 1+ year of experience with AI/ML related applications development
• Proficient in Python or C#, with a strong focus on applying software engineering best practices.
• Eagerness to learn prompt engineering, AI safety/guardrail development, and large‑scale AI deployment.
• Hands‑on experience of REST APIs development and a good understanding of cloud environments (
  Azure, AWS or GCP
  )
• Good organizational, analytical and problem‑solving skills

• Experience with CI/CD tools such as Cloud Bees, Jenkins
  , and Urban Code
  .
• Experience or familiarity with Snowflake
  , a leading cloud data platform
• Experience with Generative AI and LLM
  s (e.g.,
  GPT, Claude, Llama
  ), including related technologies such as vector databases, embeddings, prompt engineering, and agentic AI
  .
• Hands‑on experience to execute full‑stack development for GenAI deep‑research applications generating professional reports, designing high‑performance RAG pipelines
  .
• Strong proficiency in developing AI‑Powered big data processing frameworks to enable natural language‑based data frame processing. Delivering capabilities comparable to advanced text-to-SQL systems is a plus.
• Experience in optimizing LLMs' efficiency (e.g.
  LoRA
  /adapters, distillation, quantization, prompt caching) and cost control strategies (like maximizing prefix cache hit rates) is a plus.
• Understanding the Investment Risk system is an asset.

NOTE:

We leverage AI-driven solutions to streamline and enhance our recruitment process.