Medfar
Healthcare
GenerativeAI(GenAI)|PromptEngineer
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“Generative AI (GenAI) | Prompt Engineer at Medfar. Skills: Generative AI, Prompt Engineering, LLM evaluation. Audit and re-architect CoeurWay's existing monolithic prompts. Improve prompt robustness”
Industry & Context.
Break complex problems into sub-problems
Reside in Quebec, Occasional in-office presence
What They're Looking For.
Must Have
5+ years of professional experience in AI/ML, product development, computational linguistics, or related field, 2+ years of hands-on prompt engineering experience in production LLM systems, Demonstrable experience decomposing complex prompts into modular, chained architectures, Experience designing or significantly improving LLM evaluation frameworks, Familiarity with frontier commercial LLM APIs, Advanced proficiency in English, Advanced proficiency in French
Nice to Have
Experience working within or alongside healthcare, clinical, or life sciences domains, Proficiency in Python or another scripting language, Experience with self-hosted or open-weight models
What You'll Do.
Audit and re-architect CoeurWay's existing monolithic prompts
Improve prompt robustness
Improve prompt debuggability
Improve prompt adaptability
Lead selection of language models
Evaluate language models
Pair language models to prompt tasks
Own quality of AI-generated clinical outputs
Define what 'good' looks like
Identify failure modes
Drive continuous improvement
Evolve evaluation framework
Improve framework coverage
Improve framework automation potential
Align framework with clinical ground truth
Establish systematic approach to output validation
Perform regression testing for prompt changes
Document known limitations
Implement new prompts
Design evaluation suites
Implement evaluation suites
Ensure prompts are production-ready
Develop deep understanding of clinical workflows
Understand needs of healthcare providers
Maintain close relationships with client-facing teams
Stay current on LLM landscape
Bring relevant findings back to team
Contribute to internal documentation
Contribute to internal standards
Contribute to best practices for prompt engineering
Mentor future prompt designers
Participate in hiring decisions
How You'll Work.
Team & Collaboration
Product designers; Developers; QA teams; Client-facing teams; GenAIOps
Communication Scope
Nuanced AI quality concepts
Full Job Description
MEDFAR Clinical Solutions was founded in 2010 by two aeronautical engineers who realized that the healthcare system was not exploiting the full potential of technology. Supported by a large community of medical experts and focused on clinical success and patient safety, MEDFAR was the first company to certify a cloud-based Electronic Medical Record in Canada: MYLE (Make Your Life Easy). Committed to promoting excellence and effectiveness in healthcare worldwide, MEDFAR differentiates itself by offering a unique healthcare management solution for clinics, which replaces inefficient processes with a faster and safer technological alternative. As a Senior Prompt Designer, you will play a defining role in shaping the quality, reliability, and evolution of MEDFAR's generative AI features — most notably [CoeurWay](https://www.careway.ai/en), our AI-powered clinical scribe, and emerging AI capabilities within MYLE EMR. Reporting to the Director of UX, you will sit at the intersection of product, clinical quality, and AI craft, working closely with product designers, developers, QA, and client-facing teams to ensure that every AI-generated output meets the high standards required in a healthcare setting. This is a senior individual contributor role with a clear growth path toward mentoring and leading a prompt engineering practice as MEDFAR's AI product surface expands. Main Responsibilities * Audit and re-architect CoeurWay's existing monolithic prompts into a modular chain of focused, maintainable prompts — improving robustness, debuggability, and adaptability. * Lead the selection, evaluation, and pairing of language models to specific prompt tasks, fostering a model-agnostic approach that reduces vendor dependency and optimizes for quality and cost. * Own the quality of AI-generated clinical outputs: define what "good" looks like, identify failure modes, and drive continuous improvement through structured validation processes. * Evolve and re-align our existing evaluati
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