AI Solutions Developer

Ts-Imagine; Montreal (administrative region); On-site; CAD 120,000 - 160,000; Full time

Benefits offered by this job

Unlimited vacation

3 personal days

Annual bonus

Training budget

RRSP matching

Public transit subsidy

Global team with 10 offices

Job summary

TS Imagine is seeking an AI Solutions Developer to design data models, build pipelines, and semantic layers powering TSIQ across trading, risk and prime brokerage data. You’ll develop AI agents with prompt/context engineering and govern their outputs for reliability.

Join our data-driven, global Data & Analytics Office, with an on-site Montreal role four days a week and one flexible day. Competitive pay, training budget, and benefits await.

Qualifications

• Strong SQL skills and hands-on experience with Snowflake.
• Proficiency in Python, including production-grade codebases.
• Experience designing data models and building data pipelines (dbt).
• Semantic modeling experience—defining metrics, dimensions, business logic.
• Prompt engineering and context engineering for reliable AI outputs.

Responsibilities

• Design and build the data models and pipelines that power TSIQ.
• Develop semantic models so AI agents reason over trading, risk, and prime brokerage data with precision.
• Build, test, and iterate on AI agents using prompt and context engineering.
• Implement guardrails, evaluation, and governance controls for accuracy and auditability.
• Deliver analytics and rapid prototypes in Streamlit to demonstrate capabilities early.
• Gather requirements from stakeholders, translate into designs, and validate against real questions.
• Collaborate with a global team of developers in a fast-paced, innovative setting.

Job description

What if your users could simply ask? We’re building TSIQ, an AI-powered analytics and intelligence platform that answers questions, recommends actions, and runs workflows for the people who use TS Imagine’s Trading, Risk and Prime Brokerage products. As an AI Solutions Developer you’ll build both the foundation and the intelligence on top of it—the data models, pipelines, and semantic layers that make our data trustworthy, and the AI agents that turn it into answers. You'll be part of our dynamic Data & Analytics Office, a globally distributed, high-impact team that processes trillions of data points and manages our cutting-edge data lake built on Snowflake.

This is an opportunity to work at the intersection of data engineering, semantic modeling, and applied AI—on a product that is being defined as you build it. We have multiple openings across levels, from intermediate through senior.

Why You’ll Love This Role

This position is perfect for:

• Data Modelers: You believe a great answer starts with a well-designed model, and you take pride in structuring data so others can trust it.
• Applied AI Builders: You’re fluent in prompt and context engineering, and you’re energized by making AI agents reliable rather than merely impressive.
• Analytical Minds: You enjoy delving into complex data sets and ensuring the highest quality for accurate decision-making.
• Problem Framers: You’re comfortable sitting with a business stakeholder, untangling a vague request, and turning it into something buildable.
• Storytellers: You're comfortable presenting complex data and AI-driven insights in a way that engages and excites stakeholders.
• Action Takers: You thrive on challenges, taking ownership of a variety of responsibilities to deliver high-quality results.
• Lifelong Learners: You're always eager to step outside your comfort zone and dive into the intricacies of one of the most complex business domains.
• Collaborative Teammates: You possess the technical and interpersonal skills to excel in a cutting-edge software development environment.

What You’ll Do

• Design and build the data models and pipelines that power TSIQ.
• Develop semantic models so that AI agents reason over trading, risk, and prime brokerage data with precision and consistency.
• Build, test, and iterate on AI agents using prompt engineering and context engineering.
• Implement guardrails, evaluation, and governance controls that keep AI agents accurate, safe, and auditable.
• Deliver analytics and rapid prototypes in Streamlit to put capabilities in front of users early.
• Perform business analysis—gather requirements from stakeholders, translate them into technical designs, and validate that what we ship answers the real question.
• Collaborate with a global team of developers in a fast-paced, innovative setting.

What You Bring

• Strong SQL skills and hands-on experience with Snowflake.
• Proficiency in Python, including the ability to contribute to structured, production-grade codebases—not just notebooks.
• Experience designing data models and building data pipelines, including transformation frameworks such as dbt.
• Semantic modeling experience—defining metrics, dimensions, and business logic that downstream consumers depend on.
• Practical prompt engineering and context engineering skills, with a focus on making AI outputs reliable and repeatable.
• Experience building AI agents and implementing guardrails to govern their behavior (a strong plus).
• Streamlit or comparable experience building lightweight data applications.
• Business analysis skills—requirements gathering, stakeholder engagement, and documentation.
• Exceptional communication skills. This role sits between business stakeholders and the platform, so clear written and verbal communication is essential.
• Capital markets or financial services domain experience. This is extremely important to us—understanding trading, risk, or prime brokerage workflows will set you apart.

Why Join TS Imagine?

• On-site role—4 days per week in our Montreal office, with 1 day of flexibility.
• Unlimited vacation + 3 personal days.
• Annual bonus and salary review.
• $1,500 training budget to fuel your growth.
• RRSP matching (3% company contribution).
• Subsidized public transportation (Opus & Cie).
• Join a global team with 10 offices worldwide and the opportunity to make a real impact on the financial industry.

Note: This role is not remote—applicants must be based in Montreal.