Hybrid AI Product & Automation Tooling Engineer

Croesus; Laval (administrative region); Hybrid; CAD 110,000 - 150,000; Full time

Benefits offered by this job

Hybrid work

Profit sharing

Gym on-site Laval

RRSP

Breakfast daily

Job summary

Croesus in Laval, QC, is looking for a Product Ops engineer to design, power, and operate the internal AI layer that underpins our wealth-management product stack. You will build AI agents, prompts, and tool integrations to accelerate product delivery and automate internal workflows.

You’ll work closely with Product Managers, Analysts, UX Designers, and Writers to create practical, production-ready tools while maintaining security and scalability across our internal datasets.

Qualifications

• Product mindset focused on user needs, adoption, and measurable impact.
• Demonstrable excellence in building AI tools (professional, personal, or open-source).
• Ability to ship production-ready AI tooling with secure data practices.

Responsibilities

• Design, deliver, and maintain AI agents, skills, and automations for the Product team.
• Build integrations between existing systems and AI platforms.
• Establish evaluation frameworks for quality, reliability, and security of tools.
• Iterate rapidly with internal users to move from prototype to adopted tool.

Skills

Product mindset

AI know-how

LLMs in production

Back-end Python

C#

Scripting & Data

SQL

Git

Business understanding

Communication

Security

Education

Bachelor's degree in CS/Software Eng

5+ years software development

1–4 years AI tools experience

Portfolio of projects

AI certifications (asset)

Tools

Python

C#

Git

SQL

JSON

YAML

Job description

Croesus in Laval, QC, is looking for a Product Ops engineer to design, power, and operate the internal AI layer that underpins our wealth-management product stack. You will build AI agents, prompts, and tool integrations to accelerate product delivery and automate internal workflows.

You’ll work closely with Product Managers, Analysts, UX Designers, and Writers to create practical, production-ready tools while maintaining security and scalability across our internal datasets.