Build better healthcare togetherMaple’s purpose is to meet the world's healthcare needs. We’re Canada's leading on-demand healthcare platform, connecting patients with Canadian-licensed doctors, nurse practitioners and specialists. Today, we’re proud that over 8 million patients and 7,000 businesses and government partners have access to same-day, proactive and ongoing care. We enable people to take control of their health and push the boundaries of what’s possible every day. Bold minds. Big impact. A career at Maple is about making an impact. We empower bold thinking, surround you with an inspiring team and are driven by a inspiring purpose. Here, you’ll do work that changes lives—including your own.The roleWe’re looking for a Staff Software Engineer, AI to own and ship the next generation of AI-powered healthcare experiences at Maple.You’ll work inside Product Engineering, partnering with Product, Design, Platform, Security, Privacy, and clinical experts to take ambiguous patient and provider problems from discovery to production. You’ll spend meaningful time designing, writing, reviewing, and operating production code for customer-facing AI capabilities. You’ll also help the wider engineering organization adopt the patterns that make those capabilities reliable, safe, observable, and cost-effective.This is a hands-on, senior individual contributor role for an engineer who has spent the last few years actively building AI into real products—not just experimenting with models or defining high-level standards. You’ll have direct ownership of a high-impact product area while serving as a technical leader to influence how AI is built and scaled across Maple.You responsibilitiesAs a Staff AI Engineer, you will: Own a meaningful AI product area from problem discovery and technical design through implementation, launch, monitoring, and iterationPartner with Product and Design to understand user needs, identify where AI creates real value, and turn ambiguous problems into simple, useful experiencesDesign and build production AI systems using LLMs, agents, retrieval, tool calling, workflow orchestration, and human-in-the-loop patterns where appropriateWrite production code, review designs and pull requests, debug difficult issues, and participate in operational ownership after launchEstablish practical evaluation and monitoring approaches that measure product quality, safety, reliability, latency,



and costWork with Platform Engineering to make the right decisions about shared services, model providers, infrastructure, and ownership boundariesHelp teams make sound trade-offs across user experience, clinical quality, privacy, security, reliability, and AI unit economicsTurn successful product implementations into reusable patterns that help other squads move faster and more safelyMentor engineers and raise the technical bar through collaboration, design reviews, documentation, and example-settingPartner with Security, Privacy, Legal, and Clinical stakeholders on responsible handling of PHI and secure deployment of AI capabilitiesCommunicate technical decisions and product trade-offs clearly to engineers, product leaders, executives, and cross-functional partners What success looks likeIn your first 90 days, you’ll build context on Maple’s product, users, AI capabilities, and engineering environment. You’ll partner with a product squad to ship or materially advance one meaningful AI capability, establish a pragmatic evaluation and monitoring baseline for it, and build strong working relationships with Product, Design, Platform, Security, Privacy, and clinical partners. You’ll also identify opportunities to turn what you learn into reusable engineering patternsOver your first 12–18 months,you’ll demonstrate measurable product or workflow impact from the capability you helped ship and improve its quality, safety, reliability, latency, and cost through production learning. You’ll help multiple squads ship AI features that meet Maple’s standards for product quality, safety, observability, and cost. You’ll establish reusable approaches to evaluation, agent execution, monitoring, and operational readiness while staying close to users and product outcomes as your leverage increases across the organization.What you bring 8+ years of experience building and operating production software,



with Staff-level scope or equivalent technical leadershipRecent hands-on experience shipping AI- or LLM-powered product features as part of a product engineering teamExperience taking ambiguous product problems through technical discovery, architecture, implementation, launch, and iterationStrong software engineering fundamentals and the ability to make pragmatic decisions across scalability, reliability, performance, security, and maintainabilityHands-on coding experience in a modern production language, with the ability to work across AI services and product systemsExperience designing APIs, data flows, services, integrations, or distributed systems that operate in productionA product mindset: you care about who uses what you build, what outcome it creates, and how it improves over timeProven ability to influence technical direction across teams without relying on formal authorityExperience mentoring engineers and improving how teams design, build, test, and operate softwareClear written and verbal communication, including the ability to explain technical trade-offs to non-technical partners Play to your strengths. Finding the right fit goes both ways—so this section is yours to complete. When you join, you'll add the unique strengths you bring that aren't captured above.Our technology environmentWe use a mix of product engineering, AI, and platform technologies, including:AI and application development Lang Chain and Lang Graph for orchestration and agent workflowsCopilot Kit for generative UI patternsAWS Bedrock, Open AI, Anthropic, and other model providersLang Smith and Langfuse for tracing, telemetry, evaluation, and prompt iterationClick House and Postgre SQL for evaluation datasets, analytics, and AI-related data pipelines Platform and infrastructure Laravel and PHP across the core product platform, with specialized AI services and pipelinesMy SQL, Amazon Document DB, Typesense, and RedisContainerized, auto-scaling AWS infrastructure defined with TerraformGit Hub Actions, Datadog, and Bug Snag The exact tools will evolve. We value architectural fundamentals, systems thinking, and the ability to choose the right level of complexity over familiarity with a particular framework.How we'll support youWe recognise our people's health is everything. That's why we take care of them. Maple for you and your family: 24/7 access to general practitioners, pediatrics and mental health therapy for you and your family. Care starts on day oneComprehensive health coverage: Medical, dental and life insurance because your peace of mind—and your loved ones—matter mostHealth spending

📌 Staff Software Engineer, Ai (Toronto)
🏢 Maple
📍 Toronto