Sr AI Engineer

Job Description

Insight Global is leveraging Generative AI and Machine Learning to automate workflows and deliver high‑impact outcomes for Capital Markets front‑office and business teams. Use cases are driven by business stakeholders and may span decision support, workflow automation, document intelligence, data augmentation, advisor or trader tooling, and other opportunities where AI can reduce friction, improve speed, or enhance decision‑making. The successful candidate will be on site in Montreal, Toronto or Vancouver 2 days on site, knowing it may be 4 later in 2026.

We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances.

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• ~10 years of overall software engineering experience, including 4–6 years working with AI/ML systems
• Strong hands‑on programming experience with Python and modern backend frameworks (e.g., FastAPI or similar)
• Practical experience with Generative AI and LLM systems, including agents and RAG‑based architectures
• Experience deploying and operating AI/ML solutions in production or enterprise environments
• Familiarity with cloud platforms (Azure preferred; AWS exposure acceptable)
• Experience integrating APIs and connecting AI solutions to internal tools and data platforms
• Understanding of CI/CD, containerization, and basic MLOps practices
• Comfortable working in ambiguous problem spaces and in a client‑ or stakeholder‑facing capacity Experience with LLM tooling or frameworks such as OpenAI APIs, Hugging Face, Lang Chain, or similar
• Exposure to model orchestration or AI platform patterns (e.g., model routing, versioning, experimentation)
• Familiarity with financial services, Capital Markets, or regulated enterprise environments
• Understanding of data security, governance, and compliance considerations for AI systems
• Experience integrating AI outputs into dashboards, analytics, or reporting tools