Applied Ai Developer Iii (Ai Laboratory)

For over 40 years, LGI has built software that healthcare organizations depend on. AI is now at the heart of that work, not as a destination, but as the engine behind our next generation of mission-critical solutions and our enduring mission: helping healthcare organizations perform at their best.
We’relooking for exceptionalpeoplewho are passionate about technology, relentless in their standards, and driven to pushwhat’spossiblefurther. At LGI, curiosityisn'ta nice-to-have,it'show we work.We’relooking fortalentwho explore and innovate by instinct and want their work to matter beyond the codebase, shaping decisions, enhancing processes, and enabling healthcare practitioners.
Job DescriptionAs 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.
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.
QualificationsProfile & 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
A workplace built on trust,autonomyand collaboration.
The opportunity to grow, perform and work alongside curious and talented colleagues.
A continuous learning culture with dedicated training time, arenowedskills development platform and access tocutting-edgetools.
Stimulating projects thatadvancehealthcare 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 familyassistanceprogram, and a minimum of 3weeks vacationper year
At LGIHealthcare Solutions, we value diversity and equal access to employment.
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