Mid-Senior AI Engineer - QE Skilled

In this innovative hybrid role, you will bridge the gap between advanced artificial intelligence development and modern Quality Engineering (QE) practices. Sitting at the sweet spot of 7 to 10 years of total software engineering experience, you will act as a core executor—developing AI-native applications while simultaneously building specialized tools, automation scripts, and EVALs frameworks to empower the broader QE community. This position is ideal for a full-stack developer who natively builds using AI frameworks (e.g., LangChain, LangGraph, MCPs, and advanced RAG architectures) and views software design through the lens of quality, standardization, and platform reliability.

Duration: 6-Month Contract (with high potential for extension)

Work Arrangement: 100% Remote



Advantages

100% Remote Flexibility: Enjoy full remote working autonomy from anywhere within the region.

Cutting-Edge AI & QE Fusion: Work at the forefront of AI development by building tools that directly shape how Quality Engineering and automation are executed across an enterprise ecosystem.

Hands-On Platform Impact: Own end-to-end features—from designing RAG pipelines and agent behaviors to deploying robust EVALs frameworks that test and validate AI model outputs.

Modern Developer Sandbox: Deepen your technical toolkit working with modern full-stack architectures, cloud-native AI services, and next-generation testing tools.




Responsibilities

QE Tooling, EVALs & Automation Leadership
QE Productivity Tooling: Design, build, and deploy specialized tools and utilities that enhance the day-to-day productivity and technical capability of the Quality Engineering community.

Systematic EVALs Frameworks: Architect and advance robust EVALs frameworks to systematically evaluate, benchmark, test, and validate AI platform outputs for accuracy, performance, and reliability.

Ecosystem Standardization: Define and establish unified standards for test case generation, test automation scripts, and QE technical specifications using AI-assisted SDET methodologies.

AI Engineering & Full-Stack Development
AI & Agent Architecture: Develop AI-driven features, engineer intelligent agent behaviors, and build Retrieval-Augmented Generation (RAG) pipelines utilizing LangChain, LangGraph, and Vertex AI (or equivalent AWS/Azure services).

MERN Stack Execution: Write clean, modular, and performant code across the full software development lifecycle utilizing MongoDB, Express, React, and Node.js / TypeScript.

API & Backend Integration: Build, integrate, and maintain high-performance RESTful APIs, web services, and database connections using Python and Node.js.

SDET & Automation Scripting: Write automated test suites using modern web testing frameworks (e.g., Playwright or Cypress.io) powered by AI capabilities.


Qualifications

Experience Level: 7–10 years of hands-on professional software engineering and quality development experience (explicitly focused on practical execution rather than high-level architecture).

Full-Stack Development (5+ Years): Active, full-lifecycle experience with the MERN Stack (MongoDB, Express, React, Node.js / TypeScript) alongside standard enterprise dev tools (Docker, Git, VS Code, npm/pip).

AI & Cloud Ecosystems: Hands-on experience developing AI capabilities, agent workflows, and RAG architectures within Google Cloud Vertex AI (or equivalent AI platforms on AWS / Azure). Direct experience with LangChain, LangGraph, or Model Context Protocols (MCPs) is essential.

Core Backend & Scripting: Strong proficiency in Python for backend service integration, API development, and data manipulation, with secondary exposure to enterprise backend environments like Java.

QE Pedigree & SDET Capabilities: Demonstrable experience in an active Quality Engineering or SDET role with a solid grasp of modern QA concepts, automated testing frameworks, and script development (prior experience with Playwright or Cypress.io is highly valued).

Soft Skills: Outstanding problem-solving skills, strong technical communication, and a proactive mindset focused on empowering peer developers and quality engineers.



Summary
If you are a tech-savvy Software Engineer who pairs an absolute command of full-stack MERN development and modern AI frameworks (Vertex AI, RAG, LangChain) with the Quality Engineering pedigree required to build enterprise EVALs and automated testing tools, this 100% remote 6-month contract is an outstanding opportunity. Bring your hands-on execution mindset, AI scripting precision, and collaborative team focus to our client's growing engineering group today!

Randstad Canada is committed to fostering a workforce reflective of all peoples of Canada. As a result, we are committed to developing and implementing strategies to increase the equity, diversity and inclusion within the workplace by examining our internal policies, practices, and systems throughout the entire lifecycle of our workforce, including its recruitment, retention and advancement for all employees. In addition to our deep commitment to respecting human rights, we are dedicated to positive actions to affect change to ensure everyone has full participation in the workforce free from any barriers, systemic or otherwise, especially equity-seeking groups who are usually underrepresented in Canada's workforce, including those who identify as women or non-binary/gender non-conforming; Indigenous or Aboriginal Peoples; persons with disabilities (visible or invisible) and; members of visible minorities, racialized groups and the LGBTQ2+ community.

Randstad Canada is committed to creating and maintaining an inclusive and accessible workplace for all its candidates and employees by supporting their accessibility and accommodation needs throughout the employment lifecycle. We ask that all job applications please identify any accommodation requirements by sending an email to accessibility@randstad.ca to ensure their ability to fully participate in the interview process.

This posting is for existing and upcoming vacancies.