AI Augmented Developer (RAD)

LGI Healthcare Solutions Santé Inc.•Montreal, QC

About The Position

Artificial intelligence is at the heart of how we design, modernize, and evolve our healthcare solutions. AI tools, models, and practices are advancing at a rapid pace, and we are looking for ambitious, curious developers who can learn quickly and continuously adapt to change.

Requirements

A minimum of 8 years of development experience with C#, .NET, Windows Forms, application services, and Oracle (PL/SQL).
A fast, self-directed learner who explores, experiments, and continuously improves without requiring step-by-step guidance, and who can quickly adapt as technologies and ecosystems evolve.
Regular user of AI-powered development tools, with the ability to leverage AI to deliver measurable productivity gains.
Ability to critically assess and validate AI-generated outputs.
Intellectual curiosity, an interest in complex systems and architectures, and a genuine desire to understand how things are designed and built.
Strong foundations in object-oriented programming and algorithmic thinking.
Excellent communication and collaboration skills: Able to clearly explain your reasoning, seek help when needed, and actively contribute to technical discussions, even in complex situations.
Values collective intelligence and teamwork to accelerate problem-solving and decision-making.
Keeps the customer and end user at the center of their thinking and decisions, and maintains a solution-oriented mindset in a constantly evolving environment.
Interested in growing within a regulated industry environment (digital health).
Ambitious and motivated to advance and grow their career.

Nice To Haves

Experience with the Delphi programming language.
Strong understanding of build and deployment pipelines.
Experience developing enterprise-grade B2B solutions.
Experience with solution architecture and modeling.
Experience developing AI-enhanced product features or integrating AI models into existing systems.
Personal projects or open-source contributions involving AI; GitHub activity and experimentation outside of work are highly valued and stand out.
Knowledge of data integration and messaging standards/protocols (e.g., HL7 v2).

Responsibilities

Develop and maintain application modules using AI and coding-assistance tools (Copilot, Cursor, Claude Code, etc.) within a technology ecosystem based on C#, .NET, Windows Forms, application services, and Oracle (PL/SQL).
Troubleshoot and resolve complex issues in a multi-technology environment with multiple system integrations.
Help modernize and scale the platform: evolve legacy components, optimize Oracle queries and data models, and refactor performance bottlenecks
Build and extend CI/CD pipelines to automate builds, testing, and deployments
Participate in code reviews, with a critical eye on AI-generated code
Keep the end user in mind: what you build is used by medical school staff, faculty, and students, and supports the training of future physicians
Take ownership of your deliverables from requirement through to production, including testing and documentation
Work within applicable Canadian privacy standards for student records (e.g., PIPEDA and provincial legislation), supported by the team
Use AI coding assistants (Copilot, Cursor, Claude Code, etc.) every day to generate, complete, and understand code across whatever part of the stack the work requires
Lean on AI to ramp up fast on unfamiliar technologies and codebases, rather than waiting to build deep single-stack expertise
Generate and critically evaluate automated tests (unit, integration, end-to-end), judging their relevance and coverage
Build AI-supported quality gates in the delivery pipeline: automated checks for compliance, accessibility, performance, and security
Use AI to read, document, and safely modernize legacy code, reducing the risk of change
Analyze logs, errors, and stack traces with AI alongside profiling tools to accelerate debugging and performance tuning
Produce and maintain technical documentation with AI tools
Write precise prompts and iterate; recognize when AI goes off track and take back control
Quickly adopt a new tool or model when it delivers measurable gains, and share your learnings with the team