Remote AI-Powered Full-Stack Engineer (LLMOps)

Lazer Technologies; Toronto; Remote; CAD 110,000 - 150,000; Full time

Benefits offered by this job

Work From Anywhere

Work / Life Balance

Employee Care: healthcare, dental, etc

Unlimited PTO

Regular Team Retreat

Job summary

Lazer Technologies, a remote-first digital product studio with a Toronto headquarters, seeks a senior full‑stack engineer to build AI-powered applications using TypeScript, React, and Node.js. You will ship production software across the stack and collaborate with senior engineers and clients worldwide.

You will design scalable data pipelines, apply MLOps practices, and tune LLM services while working with cloud providers like AWS, GCP, or Azure.

Qualifications

• 4–6 years of full stack engineering experience.
• Experience shipping production software across the stack.
• Strong knowledge of AI/LLM tooling and testing.

Responsibilities

• Engage with clients to understand problems, needs, goals, and technical environments.
• Architect, build, and ship full stack applications that leverage AI and data capabilities.
• Apply best practices in MLOps or LLMOps, including testing, monitoring, and reliability.
• Design and build scalable data pipelines and data lakes as needed.
• Communicate tradeoffs and risks transparently, supporting client decision-making.
• Collaborate with other engineers and cross-functional teams to deliver impactful results. Stay current with the latest AI trends, technologies, and tooling to bring innovation to your projects.

Skills

TypeScript

React

Node.js

Python or Go

Generative AI experience

LLM hosting/tuning

Agentic workflows

Cloud (GCP/AWS/Azure)

Job description

Lazer Technologies, a remote-first digital product studio with a Toronto headquarters, seeks a senior full‑stack engineer to build AI-powered applications using TypeScript, React, and Node.js. You will ship production software across the stack and collaborate with senior engineers and clients worldwide.

You will design scalable data pipelines, apply MLOps practices, and tune LLM services while working with cloud providers like AWS, GCP, or Azure.