Build production AI infrastructure in Canada using agent orchestration, retrieval-augmented generation, and evaluation frameworks. Focus on reliable, secure, scalable systems.

As an Applied AI Engineer, you will build and operate AI runtime infrastructure for production agent workflows. You will implement tool calling, RAG, grounding, and context retrieval systems. You will also develop evaluation harnesses, golden datasets, quality benchmarks, and safety controls. The work supports practical AI features for mission-critical customer workflows.

Key Responsibilities

Build and operate AI runtime and orchestration infrastructure

Implement RAG, grounding, and context-retrieval systems

Develop evaluation harnesses, datasets, and quality benchmarks

Integrate testing,



quality gates, and regression checks

Own production reliability, latency, cost, and failure management

Requirements

Production experience shipping LLM- or ML-powered software

Robust understanding of systematic AI evaluation methods

Ability to manage cost and latency as constraints

Clear communication with engineers, products, and customers

Pragmatic judgment focused on measurable customer value

Apply applied AI engineering expertise across runtime architecture, RAG, evaluation, safety, and dependable production delivery.

📌 Production AI Infrastructure Engineer (Winnipeg)
🏢 Jobgether
📍 Winnipeg