What We Do We build AI models to enable smaller, faster, and more successful clinical trials.
About Altis Labs 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.
The Role 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.
Our Stack Area Technologies: Nota React, Express.js, Rapid API, Hasura Graph QL, Postgre SQL, AWS ECS (Fargate), RDS, TerragruntClinical DB: Duck DB, AWS S3, TerraformInference pipeline: Ray Serve on Kubernetes, Postgre SQL, AWS EKS, RDS, S3, Terraform, Argo CDCross-cutting: Git Hub Actions, Slurm, GCP, Azure, DockerResponsibilitiesDesign and build scalable applications for data acquisition, management, and visualization using best practicesBuild and maintain features across the full stack of Nota — from React components through Graph QL schemas to Postgres query performanceDesign, deploy, and scale ML inference services on Ray Serve and Kubernetes, including model versioning, autoscaling, and observabilityArchitect and manage the cloud environment supporting data ingestion, querying, and computer vision / ML pipeline development and deploymentOwn infrastructure as code and Git Ops across multiple accounts and environments (Terraform, Terragrunt, Argo CD)Build CI/CD pipelines that let researchers ship models without filing ticketsHandle medical imaging data at scale: DICOM ingestion, de-identification, format conversion,



and reliable movement of terabytesWork closely with the product team and external stakeholders to shape engineering goals and requirementsQualifications5+ years of software engineering experience with a track record of building and operating applications in productionFull-stack depth across front-end, back-end, database design, and software/network security — equally comfortable debugging a React render loop and a Postgres query planProduction Kubernetes

experience:
designing what runs on it and why, not just kubectl applyDeep infrastructure-as-code practice with Terraform (Terragrunt a plus) and Git Ops deployment patternsComfort operating in mixed environments: multi-cloud (AWS primary, GCP/Azure secondary) and HPC schedulers like SlurmFluency in Python and Type Script/Java Script; experience with React, Graph QL, and DockerMature CI/CD instincts: Git Hub Actions, reproducible builds, environment parityExcellent written and verbal communication skills in EnglishNice to HaveExperience in the medical technology domain (DICOM, PACS, de-identification, or clinical trial imaging)Familiarity with computer vision and machine learning applications/pipelinesExperience with Ray (Ray Serve, Ray Data, or Ray Train) in productionExperience serving deep learning models with real latency and throughput requirementsFamiliarity with regulated environments (HIPAA, GDPR, SOC 2, or FDA-regulated software)Bachelor's degree in engineering, computer science, or a related fieldAgentic Engineering We're an AI-native engineering team, and we treat this as a real skill rather than a résumé line. You should have opinions about:Working effectively with Claude Code (or comparable agentic tooling) on large, existing codebasesStructuring repositories, context, and documentation so agents produce production-quality outputBuilding custom tooling — MCP servers, skills, subagents, hooks — where it earns its keepWhere agents should be trusted, where they should be reviewed, and how to tell the differenceIf you'v

📌 Senior full-stack software engineer (Toronto)
🏢 Altis Labs
📍 Toronto