Applied AI Developer 3 - AI Laboratory

Job Description

*** Bilingualism (English and French) is mandatory. Interviews are conducted mostly in French ***

As an Applied AI Developer III within LGI's AI Lab, you will design and deploy artificial intelligence components integrated into LGI's healthcare solutions. As part of a small multidisciplinary team dedicated to applied AI, your work will focus on one or more of the following areas: AI application development and model integration, data architecture and RAG systems, and/or AI deployment and operations (LLMOps).

This is not a fundamental research position. You will explore and prototype solutions in an environment where selected approaches may ultimately be integrated into production products, subject to real-world requirements related to compliance, performance, and data sovereignty. The role is primarily focused on experimentation and demonstrating what is possible with today's AI technologies in response to the practical needs of healthcare professionals.

What You'll Do

AI Prototyping & Development

• Build prototypes, assess technical feasibility, and iterate rapidly to validate concrete AI use cases.
• Develop AI-powered features and services integrated into LGI products, including information extraction, clinical summarization, decision support, documentation generation, and more.
• Integrate LLMs and model APIs into existing product workflows while evaluating and optimizing cost, quality, and latency.
• Test and support the production deployment of AI applications developed within the AI Lab.

Data, Quality & RAG Architecture

• Design and implement RAG (Retrieval-Augmented Generation) pipelines for semantic search and contextual generation across structured and unstructured clinical and administrative data.
• Build and maintain data ingestion, indexing, and structuring pipelines while ensuring data quality, freshness, traceability, and governance, in compliance with Quebec's Law 25 and PIPEDA requirements.
• Develop NLP components for extraction, analysis, classification, and structured output of medical texts and healthcare data.

Deployment, Operations & LLMOps

• Build and maintain AI deployment pipelines, including CI/CD processes, model versioning, prompt management, and tooling.
• Monitor model quality, performance, and costs; identify reliability, security, and incident management requirements, including rollback and escalation strategies.
• Establish evaluation metrics for AI pipelines, including relevance, hallucination rates, latency, and model drift.
• Maintain thorough technical documentation of architectures, design decisions, and operational practices.

Collaboration & Knowledge Sharing

• Work closely with LGI's R&D, Product, and Architecture teams.
• Participate in AI technology monitoring and contribute to the definition of standards, best practices, and governance frameworks.

Types of Projects in the AI Lab

Depending on ongoing initiatives and your background, you will explore different approaches, build prototypes, and evaluate their potential before contributing to the incubation and integration of the most promising solutions.

Projects may include:

• Adding new capabilities to our products using LLMs, specialized or predictive models, AI services, and optimization algorithms.
• Leveraging structured and unstructured data to make information more accessible and actionable through ingestion, semantic search, and RAG-based approaches.
• Automating tasks and business processes, extracting and transforming information, and supporting decision-making.
• Experimenting with and comparing various models, architectures, and approaches to assess quality, reliability, latency, cost, and security implications.
• Evolving promising prototypes into robust, observable, and product-ready solutions that can be seamlessly integrated into LGI's offerings.

Qualifications

Profile & Core Competencies

• Strong technical curiosity and a genuine interest in AI, experimentation, and continuous learning.
• Self-driven and resourceful, with the ability to thrive in an environment where solutions and processes are not always predefined.
• Versatility and the ability to work across multiple layers of a solution stack.
• Experimental and pragmatic mindset, capable of rapidly prototyping, testing hypotheses, and adapting based on results.
• Strong critical thinking skills and rigorous judgment, particularly when evaluating outputs generated by AI systems.
• Commitment to quality, performance, and reliability.
• Ability to collaborate effectively within a small multidisciplinary team.
• Bachelor's degree in Computer Science, Software Engineering, Data Science, or a related field, or equivalent practical experience.

Required Qualifications

• 5+ years of experience developing robust software applications or services, with a solid understanding of designing resilient and maintainable solutions.
• Demonstrated experience in at least one of the following areas:
  • LLM and AI model integration
  • Data engineering and RAG architectures
  • AI deployment, MLOps, or LLMOps

• Strong understanding of data quality, transformation, traceability, and governance considerations in AI systems, including appropriate levels of human oversight.
• Recent hands-on experience with AI solutions and modern AI development tools (e.g., Claude Code, OpenCode, Codex, MCP, Skills) and the ability to critically assess their outputs, strengths, and limitations.
• Strong proficiency in Python and the modern AI ecosystem.

Preferred Qualifications

• Technical portfolio, personal or professional projects, open-source AI contributions, or a GitHub profile showcasing relevant achievements.
• Experience in digital health or other regulated industries; familiarity with HL7 v2, FHIR, Quebec's Law 25, and PIPEDA.
• Experience with sovereign or on-premises AI deployments (e.g., Ollama, vLLM, Azure OpenAI on private infrastructure); familiarity with MLOps/LLMOps practices and fine-tuning techniques such as PEFT and LoRA.
• Backend development experience with C#/.NET to facilitate collaboration with LGI product teams.
• Experience with technical components commonly associated with AI applications, such as:
  • Data ingestion and transformation pipelines (ETL)
  • Vector databases and semantic search technologies
  • Natural Language Processing (NLP)
  • Algorithmic optimization techniques
  • AI orchestration frameworks (e.g., LangChain, LlamaIndex, Hugging Face Transformers)

Additional Information

Why join LGI? 

• A workplace built on trust, autonomy and collaboration.
• The opportunity to grow, perform and work alongside curious and talented colleagues.
• A continuous learning culture with dedicated training time, a renowed skills development platform and access to cutting-edge tools.
• Stimulating projects that advance healthcare technology and support the work of over 320,000 professionals, benefiting more than 6 million patients.
• A comprehensive benefits package including group insurance from day one, a group RRSP with employer contributions, 24/7 telemedicine, an employee and family assistance program, and a minimum of 3 weeks vacation per year 

At LGI Healthcare Solutions, we value diversity and equal access to employment.