Senior Full-Stack Software Engineer

What We Do

We build AI models to enable smaller, faster, and more successful clinical trials.

We build AI models to enable smaller, faster, and more successful clinical trials.

Altis Labs is a computational imaging company focused on improving how oncology trials measure treatment benefit. Our core technology is IPRO, an AI model that generates patient-level outcome predictions directly from routine medical imaging data. Our global biopharma customers use IPRO to predict efficacy, navigate billion-dollar development decisions with confidence, and move their most promising therapies through Phase I–III trials faster.

IPRO is trained on the industry’s largest real-world imaging, clinical, and outcomes database, containing over 210 million longitudinal images and more than one million patient-years of linked outcomes.

Our multidisciplinary team of AI scientists, clinicians, and business operators is on a mission to get the most effective treatments to patients sooner. We collaborate closely with academic medical centers and co-publish our results at top-tier medical conferences.

Altis is headquartered in Toronto, serves 6 of the top 20 global biopharmaceutical companies, and is backed by leading life sciences and technology investors.

Altis Labs is recruiting a Senior Full-Stack Software Engineer with an entrepreneurial, product-focused mindset. You'll design and implement testable, scalable code as we expand our internal tooling and web-based software product — building critical features from the ground up and delivering efficiently without bureaucracy. We're looking for someone who can wear many hats. Concretely, you'll own large parts of two areas:
Nota, our clinical annotation and data-curation platform, and the ML inference infrastructure that serves our imaging models in production. Responsibilities are dynamic and will expand as we grow to meet our team's and clients' needs.

Area Technologies: Nota React

• Express.js
• FastAPI
• Hasura GraphQL
• PostgreSQL
• AWS ECS (Fargate)
• RDS
• Terragrunt

Clinical DB: DuckDB

• AWS S3
• Terraform

Inference pipeline:
Ray Serve on Kubernetes

• PostgreSQL
• AWS EKS
• RDS
• S3
• Terraform
• ArgoCD

Cross-cutting:
Git Hub Actions

• Slurm
• GCP
• Azure
• Docker

• Design and build scalable applications for data acquisition, management, and visualization using best practices
• Build and maintain features across the full stack of Nota — from React components through GraphQL schemas to Postgres query performance
• Design, deploy, and scale ML inference services on Ray Serve and Kubernetes, including model versioning, autoscaling, and observability
• Architect and manage the cloud environment supporting data ingestion, querying, and computer vision / ML pipeline development and deployment
• Own infrastructure as code and Git Ops across multiple accounts and environments (Terraform, Terragrunt, ArgoCD)
• Build CI/CD pipelines that let researchers ship models without filing tickets
• Handle medical imaging data at scale: DICOM ingestion, de-identification, format conversion, and reliable movement of terabytes
• Work closely with the product team and external stakeholders to shape engineering goals and requirements

• 5+ years of software engineering experience with a track record of building and operating applications in production
• Full-stack depth across front-end, back-end, database design, and software/network security — equally comfortable debugging a React render loop and a Postgres query plan
• Production Kubernetes experience: designing what runs on it and why, not just kubectl apply
• Deep infrastructure-as-code practice with Terraform (Terragrunt a plus) and Git Ops deployment patterns
• Comfort operating in mixed environments: multi-cloud (AWS primary, GCP/Azure secondary)…