Senior Software Engineer
Randstad Digital
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.
#J-18808-Ljbffr
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.
#J-18808-Ljbffr
Reference: WJ-3875_12767756