The Opportunity

We're at an exciting point: agentic automation is moving from prototype to production, and we need a senior engineer who can own high-impact work end-to-end. You'll turn ambiguous goals into shippable milestones, operate what you build in production, and iterate fast based on real customer feedback — all in a team that moves quickly without sacrificing reliability. About MedMe Health

At MedMe, we are passionate about empowering pharmacists to provide services beyond just prescribing. Our mission is to build an all-in-one cloud-based platform that enables pharmacists to schedule, document, and manage clinical services at scale. With over 4,500 pharmacies using our software, we've facilitated more than 25 million patient services, transforming pharmacies into community health hubs across North America. What You'll Do

Take primary ownership of a major capability (e.g., outbound/inbound concierge workflows, clinical assistant experiences, or a core LLM/voice platform subsystem) within your first 90 days

Ship hardening improvements into production — monitoring/alerts, runbooks, safer rollout strategies, and top error/latency reductions

Improve our LLM and voice agent workflows through durable architecture changes: tool boundaries, guardrails, and eval-driven iteration

Turn ambiguous asks into shippable milestones with transparent communication and tight iteration loops — reduce "stuck" work for the team

Help the team scale delivery without losing speed by establishing better patterns, defaults, and maintainability standards

Raise the bar on operational maturity: incident follow-through, observability, and reliability





Contribute to security and compliance maturity through secure-by-default practices and sound judgment

About You

Must-have: Strong backend engineering fundamentals: TypeScript/Node services, API design, data modelling

Practical full-stack fluency — comfortable contributing in React/FE when needed, not a specialist

Hands-on experience integrating with LLMs or agent frameworks and building production workflows around them (evaluation, observability, safety)

Comfort operating production systems: debugging, incident response, monitoring, and follow-through

A track record of owning projects end-to-end — scope → design → build → ship → monitor → iterate

Strong written and verbal communication; able to join customer calls, debug issues from real workflows, and translate feedback into clear engineering plans

Nice-to-have: Experience building voice agent workflows (call flows, state management, reliability patterns) and integrating with vendors like Retell

Experience with speech-to-text workflows and vendors like Deepgram

Security/compliance-adjacent experience: threat modelling mindset, secure defaults, safe data handling

Front-end test automation and/or build/deploy automation experience

AWS/GCP and production operations experience

Comfortable using AI dev tools day-to-day (Claude/Claude Code, Gemini, CodeRabbit, LangSmith, etc.) while maintaining quality and safety





Success in This Role Looks Like

30 days:

You've taken ownership of a major capability, shipped your first production improvement, and have a clear picture of where the biggest gaps are

60 days:

You're iterating autonomously — turning ambiguous asks into milestones, closing incident/feedback loops, and improving observability across the stack

90 days:

A production capability is noticeably more reliable and maintainable because of your work; the team is moving faster as a result

Long-term:

You're setting the engineering bar — better patterns, tighter operational discipline, and a system that scales without needing heroics

How We Hire

MedMe is committed to a fair and equitable hiring process for all candidates. To ensure that each candidate's journey is consistent and the selection process is unbiased, the team at MedMe will not be responding to any personal messages regarding this role or other opportunities. This role will follow the below Interview Process: Initial screening conversation with the recruiter

Intro call with the hiring manager

Technical interview with the team

Product chat with our product manager

References and offer

How We Use AI

At MedMe, we use AI to help us organize and manage applications, so our team can spend their time where it matters most. Every CV is personally reviewed by a human being; AI helps us stay organized, not make decisions. We believe AI should make great people more effective, not replace the thinking and judgment that great hiring requires. Perks at MedMe

Comprehensive Health Benefits:

Full coverage for dental, vision, physical, and me

📌 Sr. Full Stack Software Engineer (Toronto)
🏢 MedMe Health
📍 Toronto