Senior Software Engineer

Number of openings: 1, 12-Month initial contract

Location: Toronto, ON CA

Hybrid work — 4 days/week in-office downtown Toronto

Must be eligible to work in Canada

Roles and responsibilities:

We are seeking a proactive, full-stack Python & AI Developer to join the Equities Technology team's Applied AI Initiative. In this role, you will drive an "AI-first" engineering culture by embedding modern AI tools and Agentic AI workflows directly into core software engineering practices and internal platforms.

You will be responsible for building high-impact Proofs of Concept (POCs) from scratch and scaling AI features within a secure enterprise infrastructure. We are looking for a true builder with a strong sense of curiosity and enthusiasm for modern generative AI and agentic coding workflows.

Key Responsibilities

- Rapidly build, prototype, and ship POCs that apply modern AI to real-world business challenges.

- Champion AI-assisted development and Agentic AI coding practices across the entire Software Development Lifecycle (SDLC).

- Collaborate with cross-functional technology and business teams to identify, validate, and scale high-value AI opportunities.

- Embed generative AI solutions responsibly, adhering to enterprise security, scalability, and privacy standards.

Must have Qualifications

A minimum of 5+yrs of the following:

- Python Expertise: Deep, hands-on knowledge of Python and its core modern frameworks.

- Agentic Coding & AI Tooling: Practical experience with GitHub Copilot, modern LLM-driven development tools, and agentic coding patterns.

- Full-Stack Capability: Working knowledge of modern front-end frameworks (React strongly preferred) and relational databases.

- Deployment & Enterprise Tech: Solid grasp of containerization, modern deployment patterns, and foundational enterprise architecture requirements (security, logging, scalability).

- Generative AI Concepts: Solid understanding of modern GenAI patterns (RAG, AI agents, embeddings, prompt/context engineering, evaluation frameworks).

- AI Governance & Risk Awareness: Understanding of data privacy, hallucination mitigation, model risk management, and operating within enterprise/regulated guardrails.

Preferred Experience & Mindset

- Proactive "builder" mindset with high initiative and a passion for staying on the cutting edge of AI development.

- Previous experience in regulated environments (financial services, healthcare, etc.) is a plus, though Capital Markets domain knowledge is not required.

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