Company Description Croesus provides innovative, high-performance, and secure wealth management solutions that include portfolio management systems, portfolio rebalancing tools, and application programming interfaces (APIs). These solutions empower wealth management professionals to improve their productivity, enhance their client relationships, make informed decisions, and maximize the management of their assets under management.

Croesus’s mission is to provide a superior experience to its clients, users, partners, and employees and to positively impact the community.

With more than 200 employees in its Montréal, Toronto, and Geneva offices, Croesus has won several industry awards for being a high-quality solution provider and an outstanding employer.

Position As part of the Product Ops team, you will be the driving force behind our internal technological ecosystem. Your mission: design, power, and operate the internal AI layer and data structures that transform how Croesus’ Product team (Product Managers, Product Owners, Business Analysts, Technical Writers, UX Designers) designs, delivers, and operates its wealth management solutions. As a true technology catalyst, you don’t just maintain the status quo. You place intelligent automation, agentic engineering, and advanced test data management at the heart of our processes to eliminate friction, standardize our practices, and multiply the operational efficiency of the Product team. You don't deliver PowerPoints on AI—you deliver code, agents, and concrete tools.

Main Responsibilities

- Build Product AI Tooling Design, deliver, and maintain AI agents, skills, and automations used by members of the Product team.
- Build seamless integrations between our existing systems and AI platforms.




- Establish evaluation frameworks to ensure the quality, reliability, and security of delivered tools.
- Iterate rapidly with internal users to move from prototype to adopted tool.
- Scalability of Internal Datasets Maintain and evolve the plugin architecture that allows for the injection of mock data. Design source files that enable the generation of ultra-realistic test data. Utilize the developed tools to generate datasets tailored to internal needs.
- Standardize Product Practices and Tools Ensure code quality (unit testing, maintainability, scalability). Maintain a clear inventory of internal tools, their use cases, and their dependencies. Establish best practices for the documentation, versioning, and deployment of internal tools. Document architecture, technology choices, and developments. Build usage and impact reporting (adoption, productivity gains, quality of deliverables). Ensure security and compliance across all deployed tools.
- Catalyze Adoption Collaborate with Product Managers, Product Owners, Business Analysts, Technical Writers, and UX Designers to observe their work and identify potential efficiency gains. Lead demonstration sessions, gather constructive feedback, and adjust tools accordingly. Actively contribute to the organization's AI culture—not through presentation slides, but through functional, working tools.



Any other related task aimed at optimizing the product ecosystem.

Requirements

The working language is French, all internal meetings (including interviews) at Croesus are conducted in French, so a solid proficiency in French is mandatory.

We’re looking for a "problem solver" above all else. Years of experience matter little — your ability to understand a problem, break it down, and deliver a solution that concretely works is what's most valuable.

Academic background and experience: Bachelor's degree in computer science, software engineering, or a related field, or equivalent experience.

5+ years experience in software development 1 to 4 years of experience building AI tools. A portfolio or concrete projects demonstrating hands‑on proficiency.

Academic background or specialized certifications in artificial intelligence — an asset.

Skills we're looking for:

- Product mindset: driven by automation («automate everything» mindset) and focused on end‑user needs. You think in terms of users, adoption, and measurable impact - not just «cool tech».
- AI know‑how: demonstrable excellence in building AI tools (professional, personal, or open‑source projects).
- LLMs in production: proficiency in advanced prompt engineering, language model API integration, RAG architectures, and response quality/safety evaluation frameworks.
- Back‑end: proficiency in Python and C#.
- Scripting & Data: experience using Python to manipulate, transform, and generate source files (JSON, YAML, CSV).
- Databases: knowledge of relational databases and SQL.
- Dev tools: solid knowledge of Git or similar versioning tools.
- Business understanding: ability to quickly grasp a new

📌 AI Product and Automation Tool Developer (Laval)
🏢 Croesus Finansoft
📍 Laval