Staff AI/ML Java Architect — Edge, Data & Inference

Bevertec; Toronto; On-site; CAD 110,000 - 117,000; Full time

Job summary

Bevertec is seeking a Staff/Principal Software Engineer in Toronto to drive AI/ML initiatives and backend architecture. The role demands deep Java Spring Boot expertise, significant system design input, and hands-on coding across edge, backend, and AI platforms.

You will collaborate with data science to build trust-signal processing foundations and robust inference pipelines. The ideal candidate has 10+ years in distributed systems, strong AI tooling experience, and a track record of delivering

Qualifications

• 10+ years building production distributed systems.
• Experience building features for ML inference pipelines (data normalization, feature stores, model serving).
• Green field project experience—selecting and building frameworks.
• Strong hands-on coding with AI-assisted workflows.
• Expertise in system design architecture and communicating decisions.
• Proficiency with AI dev tools (GitHub Copilot, LLM workflows, agents).
• Track record of taking systems from 0 to 1 in greenfield projects.

Responsibilities

• Own and influence system design across teams.
• Translate ambiguous product goals into technical plans and roadmaps.
• Write high‑quality code, focusing on backend Java Spring Boot implementations.
• Collaborate with data science on AI/ML platform foundations.

Skills

10+ years distributed systems

AI dev tools proficiency

Greenfield project experience

AI-assisted coding

System design architecture

Proficiency with AI workflows

Greenfield builder track record

Architectural decision communication

Tools

GitHub Copilot

LLM-powered workflows

Agentic coding assistants

Job description

Bevertec is seeking a Staff/Principal Software Engineer in Toronto to drive AI/ML initiatives and backend architecture. The role demands deep Java Spring Boot expertise, significant system design input, and hands-on coding across edge, backend, and AI platforms.

You will collaborate with data science to build trust-signal processing foundations and robust inference pipelines. The ideal candidate has 10+ years in distributed systems, strong AI tooling experience, and a track record of delivering