10+ years of experience building and operating production-scale distributed systems. Proven experience designing and developing scalable backend platforms and services. Strong understanding of software architecture, system design, and cloud-native development. Experience translating ambiguous business requirements into technical solutions and execution plans. Data & AI Platform Experience

Experience building features for ML inference pipelines. Strong understanding of: Data processing frameworks Experience enabling machine learning workloads in production environments. AI-Assisted Development

Demonstrated proficiency with modern AI development tools, including: LLM-powered engineering workflows Agentic coding assistants Ability to effectively leverage AI tools to improve code quality, engineering productivity, and development speed. Greenfield Product Development

Proven track record of taking systems and platforms from 0 to 1. Comfortable working with undefined requirements and rapidly evolving priorities. Strong ownership mindset with the ability to drive initiatives independently. Ability to lead architectural discussions and influence technical direction.



Experience communicating complex technical concepts across engineering and business stakeholders. Solid decision‑making skills around system design, scalability, reliability, and maintainability. Technical Skills

Java Spring Boot REST APIs AWS Compute, Storage, Networking IAM Cloud-native Architecture AI / Data Platforms

Databricks Programming Languages

Java Python Development Tools

AI-Assisted Development Tools Modern CI/CD Practices Ideal Candidate Profile

You will be successful in this role if you:

Have built AI-enabled platforms rather than simply consuming AI technologies. Have experience supporting ML inference and production AI systems. Use AI tools extensively to improve engineering efficiency and quality. Thrive in startup-like environments with high ownership and rapid execution. Enjoy solving complex technical challenges with limited direction. Collaborate effectively across Engineering, Product, and Data Science teams. Influence through technical excellence, architecture, and hands‑on execution.

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📌 Principal Software Engineer – AI Infrastructure (Winnipeg)
🏢 Apexon
📍 Winnipeg