Sr. Full Stack Software Engineer (Backend - AI products)

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 clear 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 rol