Sr SW Engineer, AI

Your opportunity

Our client is a pioneering, seed-stage startup on a mission to revolutionize the delivery of pharmacy care worldwide. They build a category-creating product suite of proprietary LLMs, AI agents and cloud tools that empower pharmacists to focus entirely on patient care and remedy the unsustainable situation of chronic pharmacy understaffing in a world of aging populations and declining graduation rates.

The company was founded in 2024, driven by the frontline frustrations of its co-founder and CEO, who spent six years working in community and hospital pharmacies, and the capabilities created by recent advancements in artificial intelligence and machine learning. The company is currently undergoing a period of rapid growth and transformation, and is raising a multi-million-dollar round.

The company currently has a headcount of 5 full-time employees, with 3 in engineering, including the Cofounder & CTO. The rest of the organization is in clinical program management and operations. The CEO currently leads go-to-market. They are supported by a fractional CFO, legal team and a collection of accomplished and engaged advisors. They are presently headquartered in downtown Toronto, though the founders are planning a relocation to New York City. The company will maintain an office space in both cities moving forward.

The client's product suite leverages AI, particularly LLMs and intelligent search, to deliver context-aware clinical decision support in the pharmacy setting. It effectively acts as an on-demand clinical assistant, helping pharmacists quickly navigate vast amounts of drug information and patient data. External observers have described the company as a "developer of AI infrastructure for pharmacy and life science companies" that provides powerful contextual search through millions of documents within seconds . This capability enables pharmacists to obtain precise answers and insights rapidly, thereby improving both efficiency and the quality of patient care.

Key responsibilities 

• Machine learning engineering: Design, train and fine-tune LLMs for pharmacy-specific tasks, and build and maintain the integration layers that connect these models to external systems such as REST APIs and vector databases for reliable, production-grade data retrieval and inference

• Data pipeline engineering: Build and optimize scalable pipelines that ingest unstructured medical data, apply OCR, cleaning, and normalization steps, and transform the results into standardized, high-quality datasets for both model training and real-time inference while ensuring scalability, accuracy, and regulatory compliance

• Backend software development: Write, test, and maintain scalable backend services and APIs using Python (FastAPI) and TypeScript ), ensuring clean, maintainable code, robust testing, and seamless integration with the AI platform

• Cloud infrastructure & DevOps: Manage and optimize deployments on GCP, containerize applications with Docker, and orchestrate Kubernetes clusters to ensure reliable, scalable, and secure infrastructure

• Customer collaboration: Engage directly with pharmacy partners and clinical stakeholders to gather feedback, diagnose real-world workflow challenges, and ensure development cycles deliver maximum value for customers

Tech stack

• Back-end & APIs: Python (FastAPI), TypeScript ), Vector databases

• Machine Learning: PyTorch; Retrieval-Augmented Generation (RAG) pipelines; LLM fine-tuning

• Cloud & DevOps: Google Cloud Platform; Docker; Kubernetes

Your know-how

• You have 4+ years of experience in backend or full-stack software engineering

• You have 2+ years of experience with machine learning and data engineering

• You have experience building ​​high-availability distributed systems, including infrastructure, web services, horizontally scalable systems, and performance optimization

• You have a contagious growth mindset and persistently seek opportunities to improve yourself, the team, products and processes in a scaling business

• You have an excellent command of English

It's a bonus if

• You have a bachelor's degree in computer science, software engineering, machine learning or a related technical discipline

• You have experience working on enterprise-grade software that handles sensitive data

• You have previously served in a business that faces the healthcare industry

• You have experience building or scaling a B2B SaaS startup

• You have an acute interest in pharmacy or health technology