Senior AI Engineer

Role overview A senior engineering role focused on designing and shipping production-grade agentic AI systems that integrate with enterprise platforms to automate operational workflows for large organizations and public-sector clients. The work spans the full lifecycle of LLM-powered systems — from retrieval pipelines and multi-agent orchestration to evaluation, deployment, and ongoing monitoring — alongside enterprise systems such as EAM, CMMS, and ERP suites.

Responsibilities - Architect multi-agent AI systems covering orchestration, tool use, retrieval, and evaluation that integrate with platforms like IBM Maximo, SAP, Oracle, and Archibus. - Own the end-to-end ML and LLM pipeline: data ingestion, retrieval, model selection, prompt and agent design, offline and online evaluation, deployment, and monitoring. - Collaborate with domain experts to frame operational problems as scoped AI solutions tied to measurable business outcomes. - Set engineering standards for AI quality, safety, observability, and cost control, and mentor teammates through design reviews and pair programming. - Participate directly in client pilots and deployments, including occasional on-site workshops.

Requirements - 5+ years of professional software engineering experience, with at least 2 years shipping ML or LLM-powered products in production. - Strong Python and hands-on experience with modern agent tooling such as LangGraph, LlamaIndex, and OpenAI/Anthropic/Azure OpenAI APIs, plus vector databases. - Solid grasp of retrieval-augmented generation, evaluation methodology, tool use, and agent design patterns. - Experience integrating with enterprise data sources and APIs, including SQL warehouses, REST/GraphQL, or Kafka. - Proven ability to lead technical work through ambiguous problems and communicate clearly with non-technical stakeholders. - Must be legally authorized to work in Canada.

Nice to have - Background in enterprise asset management, facilities operations, energy, or capital planning. - Experience delivering projects for government, municipalities, universities, or healthcare clients. - Familiarity with Canadian data residency and privacy frameworks such as PIPA, PIPEDA, or FOIP. - Publications or open-source contributions in ML, NLP, or agentic systems.

Benefits and work setup - Full-time senior role based in Edmonton or remote within Canada, with hybrid or remote work modes available.