Remote Software engineering Jobs · LLM

• Lead a team of full-stack engineers shipping AI-powered workflows for patients and providers.
• Partner with clinicians and product leaders to translate emerging cardiometabolic care needs into actionable engineering work.
• Coach and mentor engineers in both technical execution and cross-functional leadership.

• Establish the technical vision for our AI product infrastructure.
• Develop frameworks that make LLM integration seamless and reliable; building APIs and SDKs that allow LLMs to interface with Wealthsimple data and functionality.
• Build new AI-powered product capabilities from 0 → 1; collaborating directly with product teams to bring AI features to life.

• Building Generative AI applications for document summarization, classification, and question and answer using unstructured and structured data.
• Developing applications on Google Cloud and working with customers to understand their requirements.
• Implementing best practices and state-of-the-art techniques for AI and LLMs.

In this role, you will drive the strategic and technical direction of AI engineering across multiple product lines, shaping how advanced AI capabilities power user-facing automation experiences. You will lead high-impact engineering teams, guiding experimentation, architecture decisions, and end-to-end delivery of AI-driven solutions. Working closely with product, design, and go-to-market teams, you will help define the roadmap, unify core AI initiatives, and turn bold ideas into scalable outcomes.

Lead and mentor a team of AI engineers, providing coaching and performance feedback. Oversee the delivery of AI-powered product features, from prototypes to scalable production systems. Collaborate with Product, Design, and Data teams to ensure AI solutions are impactful and aligned with business goals.

• Explore and preprocess raw, messy datasets and design data strategies.
• Prototype model ideas and translate prototypes into production.
• Collaborate with cross-functional teams to turn ideas into impactful features.

• Design, implement, and deploy AI-powered features, including model training, fine-tuning, and prompt engineering workflows.
• Translate product requirements into robust, production-ready AI solutions, working with Product Managers, Software Engineers, and Data Scientists.
• Optimize models and infrastructure for scalability, latency, and cost efficiency, partnering with DevOps and MLOps to ensure reliable and maintainable AI pipelines.

• Lead a cross-functional team of ML engineers, data scientists, and MLOps professionals.
• Oversee the full lifecycle of LLM and ML projects — from data collection to training, evaluation, and deployment.
• Provide technical direction on large-scale model training, fine-tuning, and distributed systems design.

Lead AI and ML initiatives to design and implement production-grade machine learning systems and pipelines. Develop scalable infrastructure for model training, evaluation, and deployment, ensuring reliability and observability. Collaborate with cross-functional teams to drive innovation and efficiency.

• Lead AI engineering execution across the build organization.
• Partner with the Director of Product - AI.
• Define how millions of people experience automation in the AI era.