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Full Stack Developer, AI

Userful Corporation -
Calgary, AB

Quick apply

Job details

Full-time

Qualifications

Spring Boot
Azure
Law
CSS
React
Internet of things
Relational databases
DevOps
Responsive design
Java
Master's degree
Docker
Bachelor's
PostgreSQL
REST
UX
Software development
APIs
Linux
AI
Figma
TypeScript
Communication skills
Debugging
HTML

Full job description

Position: Full Stack Developer, AI

Location: Calgary, AB (Hybrid / On-site)

Experience Level: 4+ years; Bachelor's or Master's Degree desirable, or equivalent technical experience

About Userful

Userful accelerates digital transformation for enterprise IT with a suite of applications on a single platform. Innovating at the intersection of operations technology and unified communications, Userful improves collaboration and productivity for optimized mission-critical and core workflows. Built on IT standards and protocols, the Userful Infinity Platform is centrally managed, scalable, secure, and future-proofed. Its software-defined architecture reduces total cost of ownership (TCO) and eliminates operational silos. Userful partners with leading global companies powering a technology ecosystem that ensures seamless integrations and end-to-end interoperability. A multinational company with headquarters in Calgary, Alberta, Userful supports customers in more than 100 countries around the world.

Userful's solutions have won multiple awards, secured strategic global partnerships, and have been deployed in countless Fortune 500 and notable companies globally including Audi, HP, Samsung, LG, Unilumin, Comcast, Coca-Cola, Wayfair, Ford, Dell, the Calgary Tower, and more!

About the Role

We are looking for a high-impact Full Stack Developer to join our team. In this hands-on role, you will help turn AI capabilities into practical, operator-facing product workflows across the Userful Infinity Platform.

You will work across the full stack, building modern React/TypeScript interfaces, Java/Quarkus backend services, APIs, and AI. This role is ideal for an engineer who enjoys product execution, complex integration work, and making AI-powered features clear, reliable, and usable in real customer environments.

This is not a pure AI research role. It is a product engineering role focused on bringing AI outputs into the operator experience with quality, maintainability, and supportability.

Core Responsibilities

Full-Stack Product Delivery: Design and implement AI features across the React/TypeScript frontend and Java/Quarkus backend services.
Operator Experience: Build operator-facing views, including AI agent creation, anomaly details, history pages, recommendation summaries, technical reference displays, and review workflows.
AI and RAG Integration: Integrate AI/LLM/RAG outputs into the product, including contextual explanations, priority indicators, technical references, confidence signals, and recommendation details.
Backend and Data Flow: Support API design, PostgreSQL schema evolution, event and anomaly history, pagination, retention logic, and reliable data flow between UI and other components.
Edge-Aware Engineering: Work with Docker, Linux, Azure IoT Edge-based deployments, containers, local execution constraints, GPU-aware workflows, and intermittent connectivity.
Quality and Maintainability: Write maintainable code, participate in code reviews, document technical decisions, and work closely with QA to validate model-facing and operator-facing workflows.
Cross-Functional Collaboration: Partner with AI/ML, platform, edge, backend, frontend, QA, DevOps, UX, and product stakeholders to deliver customer-ready capabilities.

Required Qualifications

4+ years of professional software development experience in a product-driven environment.
Strong experience building responsive web applications with React, TypeScript, HTML, CSS, and modern frontend patterns.
Strong backend development experience with Java; experience with Quarkus or Spring Boot is a significant advantage.
Experience designing, implementing, and consuming REST APIs.
Experience with PostgreSQL or other relational databases.
Familiarity with Docker and Linux-based development environments.
Ability to translate Figma designs and product requirements into production-ready workflows.
Strong debugging skills across frontend, backend, data, and integration boundaries.
Clear communication skills and the ability to explain technical trade-offs to product, design, QA, and engineering stakeholders.

Preferred Qualifications

Experience integrating AI/LLM/RAG services, vector databases, prompt workflows, or AI-assisted product features.
Experience with Azure IoT Edge, distributed edge systems, or containerized applications running outside the cloud.
Familiarity with GPU-aware workflows, device management, monitoring dashboards, or operational systems.
Familiarity with AV-over-IP, multicast, VLANs, subnetting, or hardware-integrated software environments.

Professional Competencies

Product Execution: Able to take a product requirement from design through implementation, testing, and release support.
Systemic Thinking: Able to design for scale, security, reliability, maintainability, and supportability.
Autonomy: A self-starter who can clarify ambiguous requirements, propose practical implementation paths, and deliver incrementally.
Quality Mindset: Committed to readable code, useful tests, thoughtful reviews, and stable customer-facing workflows.
Communication: Comfortable working across engineering, product, UX, QA, DevOps, and leadership teams.

Why Join Our Team?

This is a hands-on full-stack role with high visibility and meaningful technical depth. You will work closely with AI, edge, backend, frontend, QA, DevOps, and product teams to deliver practical AI capabilities into the Userful Infinity Platform.

Quick apply

Refine Your Search

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About Userful

About the Role

Core Responsibilities

Full-Stack Product Delivery: Design and implement AI features across the React/TypeScript frontend and Java/Quarkus backend services.

Operator Experience: Build operator-facing views, including AI agent creation, anomaly details, history pages, recommendation summaries, technical reference displays, and review workflows.

AI and RAG Integration: Integrate AI/LLM/RAG outputs into the product, including contextual explanations, priority indicators, technical references, confidence signals, and recommendation details.

Backend and Data Flow: Support API design, PostgreSQL schema evolution, event and anomaly history, pagination, retention logic, and reliable data flow between UI and other components.

Edge-Aware Engineering: Work with Docker, Linux, Azure IoT Edge-based deployments, containers, local execution constraints, GPU-aware workflows, and intermittent connectivity.

Quality and Maintainability: Write maintainable code, participate in code reviews, document technical decisions, and work closely with QA to validate model-facing and operator-facing workflows.

Cross-Functional Collaboration: Partner with AI/ML, platform, edge, backend, frontend, QA, DevOps, UX, and product stakeholders to deliver customer-ready capabilities.

Required Qualifications

Preferred Qualifications

Professional Competencies

Why Join Our Team?

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