Senior Software Engineer, AI/ML (Remote Canada)

Responsibilities:

Be the AI/ML subject matter expert on the team. Stay abreast of emerging technologies, trends and opportunities, and infuse AI/ML strategy and best practices into our solutions.
Help document the company’s AI strategy and ensure alignment with the product roadmap and company objectives.
Help shape the approach, scope, milestones, and solution design at the project start.
Implement AI/ML solutions with the development team; write code, configure external components and prototype new technology.
Write manageable code and unit tests and create relevant documentation.
Participate in client meetings if required.
Remain acutely aware of all priorities, deadlines, and backlogs to positively coach and assist the team in completing the required project tasks.
Understand the functionality being developed to provide support to the team.
In-depth in-person code reviews, pair programming, and collaborative problem analysis.
Participate in recurring Product and/or Technology meetings to suggest or actively participate in corporate technical processes, architecture, and strategy, as required.

Requirements:

6+ years of experience in software architecture, full-stack development, or AI engineering
Proven experience designing and documenting end-to-end software architectures for complex projects
At least 2 years of experience implementing advanced AI solutions, including semantic matching, RAG systems, and document parsing for structured content
Experience designing and deploying agentic systems using frameworks such as LangGraph, Crew AI, or the OpenAI Agents SDK
Working knowledge with coding assisted platforms like Claude Code, Codex
Knowledge of Model Context Protocol (MCP), related tooling systems, model ensemble methods, and fine-tuning techniques
Usage experience with Knowledge Graph databases like Neo4j or others
Working knowledge of Apache suites like Databricks, Spark, and Iceberg or other related workflows
Experience with Human-in-the-loop (HITL) integrations within AI workflows
Experience implementing evaluation frameworks, results testing, and iterative refinement techniques for AI models
Proficient in coding best practices, including writing clean, modular code and utilizing shared internal libraries
Deep understanding of all authored code, including code generated or co-authored by AI tools
Experience writing comprehensive unit and integration tests, along with accompanying technical documentation
Ability to author clear, concise documentation that enables seamless developer onboarding and project contribution
Strong collaboration skills with a track record of owning specific development components and meeting strict deadlines
Experience mentoring team members and collaboratively brainstorming technical architectures