Senior Full Stack Developer

Finning•Edmonton, AB

2d•CA$120,000 - CA$130,000•Hybrid

About The Position

Finning Canada is looking to hire a permanent, full-time Senior Full Stack Developer who will report to the Solutions Delivery Lead in Surrey or Edmonton. The Senior Full Stack Developer is responsible for designing, building, and evolving modern digital products that deliver measurable business value. This role combines deep software engineering expertise with AI-assisted development practices, leveraging emerging technologies, cloud platforms, and agentic development frameworks to accelerate delivery while maintaining enterprise standards. The successful candidate will partner closely with business stakeholders, product owners, architects, and delivery teams to transform ideas into scalable solutions. They will utilize AI-powered development tools to rapidly prototype, build, test, and deploy solutions while ensuring security, performance, maintainability, and business alignment. As a senior member of the team, this individual provides technical leadership, mentors developers, establishes development standards, and champions modern engineering practices including AI-assisted development, DevSecOps, platform engineering, and continuous improvement.

Requirements

Post-secondary degree in Computer Science, Software Engineering, Information Systems, or equivalent practical experience.
7+ years of experience designing, developing, and delivering enterprise software solutions.
5+ years of experience building modern web applications, APIs, and distributed systems.
Experience working in Agile product delivery environments.
Experience with cloud platforms, preferably Microsoft Azure.
Expertise in modern frontend frameworks such as Angular, React, or similar technologies.
Strong backend development experience using .NET/C#, Node.js, or comparable technologies.
Proficiency in SQL and modern data platforms.
Experience developing and integrating RESTful APIs and enterprise integration solutions.
Cloud-native application development and architecture.
Microservices, event-driven, and distributed system architectures.
Enterprise integration and API management patterns.
Modern observability, monitoring, and performance optimization practices.
Git-based source control and collaborative development workflows.
CI/CD pipeline development and automation.
Infrastructure as Code (IaC).
Containerization and orchestration technologies (Docker, Kubernetes).
Automated testing and quality engineering practices.
DevSecOps and Site Reliability Engineering (SRE) principles.
Secure software development practices.
Knowledge of security, privacy, compliance, and governance requirements.
Understanding of Responsible AI development and governance principles.
Experience leveraging AI-assisted software development tools and workflows.
Prompt engineering for software design, development, and delivery.
Agentic development workflows and AI-driven automation.
AI-assisted code review, testing, optimization, and refactoring.
Rapid prototyping using AI-powered development platforms.
Human-in-the-loop validation, quality assurance, and risk management.
Ability to translate business outcomes into requirements, prompts, and production-ready solutions.
Modern software engineering methodologies, including Agile, Lean, and Product Delivery practices.
Cloud architecture patterns and scalable application design.
Enterprise integration and API management strategies.
AI-assisted software development practices and emerging engineering trends.
Security, compliance, DevSecOps, and SRE best practices.
Excellent problem-solving and critical-thinking skills
Strong communication and stakeholder management capabilities
Ability to quickly learn and adapt to emerging technologies
Strong business acumen and product mindset
Ability to balance speed, quality, security, and maintainability
Collaborative leadership and mentoring skills

Nice To Haves

Experience with GitHub Copilot, Microsoft Copilot, Cursor, Windsurf, Devin, or similar AI development platforms.
Experience building AI-enabled applications, intelligent automation solutions, or AI-powered user experiences.
Experience with Azure AI Foundry, Azure OpenAI, Copilot Studio, Semantic Kernel, LangChain, or comparable AI frameworks and services.
Experience building AI-enabled enterprise applications.
Experience with Azure AI services and modern AI frameworks.
Experience with observability and monitoring platforms.
Experience with Docker, Kubernetes, and cloud-native deployment models.

Responsibilities

Design, develop, test, and deploy modern full-stack applications and digital products
Build scalable cloud-native solutions using modern web, mobile, API, and integration technologies
Leverage AI-assisted development tools and agentic software engineering frameworks to accelerate solution delivery
Translate business requirements into secure, scalable, maintainable solutions
Perform code reviews and ensure adherence to enterprise engineering standards
Utilize generative AI, code assistants, agentic workflows, and prompt engineering techniques to accelerate development lifecycle activities
Rapidly prototype and validate business concepts through AI-assisted development approaches ("Vibe Coding")
Evaluate and recommend emerging AI technologies, frameworks, and development tools
Partner with business stakeholders to identify opportunities for AI-driven automation and productivity gains
Champion responsible AI development practices and governance standards
Provide technical guidance and mentorship to development team members
Lead architecture discussions and design reviews
Promote engineering best practices, reusable components, and platform standards
Support team capability growth in AI-assisted development and modern engineering techniques
Support production applications and resolve incidents, defects, and performance issues
Monitor application health, reliability, and security
Participate in continuous improvement of CI/CD, DevOps, and operational processes
Provide solution estimates and technical assessments
Identify risks, dependencies, and delivery considerations
Report progress and proactively escalate issues
Deliver high-quality software solutions that meet business objectives
Ensure solutions are secure, scalable, supportable, and aligned with enterprise architecture
Apply AI tools responsibly while maintaining accountability for solution quality
Ensure code, prompts, AI-generated artifacts, and configurations are properly governed and version controlled
Contribute to continuous improvement of engineering practices and delivery capabilities
Mentor and develop team members
Identify and manage technical debt and system risks
Maintain compliance with change management, security, and governance standards