Senior Full-Stack Software Engineer

Altis Labs

Toronto

On-site

CAD 120,000 - 160,000

Full time

5 days ago
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Benefits offered by this job

Equity compensation
Medical, vision, and dental insurance
4 weeks vacation

Job summary

Altis Labs, a Toronto-based computational imaging company, seeks a Senior Full-Stack Software Engineer to own large parts of Nota and ML inference infrastructure. You will design scalable, testable code and ship features from the ground up, balancing product concerns with engineering excellence.

You’ll work across React, GraphQL, Docker, and cloud services to deliver production-ready software while collaborating with clinicians and researchers to advance oncology trials.

Qualifications

  • 5+ years of software engineering experience in production
  • Full-stack depth across front-end, back-end, database design, and security
  • Production Kubernetes experience: design and reasoning beyond kubectl
  • Infrastructure-as-code with Terraform (Terragrunt a plus) and GitOps
  • Multi-cloud (AWS primary, GCP/Azure secondary) and HPC schedulers like Slurm
  • Fluency in Python and TypeScript/JavaScript; experience with React, GraphQL, and Docker
  • Strong CI/CD practices with GitHub Actions and reproducible builds
  • Excellent written and verbal communication in English

Responsibilities

  • Design and build scalable applications for data acquisition, management, and visualization
  • Build and maintain features across the full Nota stack from React to GraphQL and Postgres
  • Design, deploy, and scale ML inference services on Ray Serve and Kubernetes
  • Architect and manage cloud environments supporting data ingestion and computer vision/ML pipelines
  • Own infrastructure as code and GitOps across multiple accounts and environments (Terraform, Terragrunt, ArgoCD)
  • Build CI/CD pipelines enabling researchers to ship models without tickets
  • Handle medical imaging data at scale: DICOM ingestion and de-identification
  • Collaborate with product teams and external stakeholders to shape engineering goals

Skills

Full-stack software engineering
Python
TypeScript/JavaScript
English communication
Debugging complex systems

Education

Bachelor's degree in engineering or computer science

Tools

Kubernetes
Terraform
Terragrunt
GitHub Actions
GraphQL
Docker
React
PostgreSQL
AWS
GCP
Azure

Job description

What We Do

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

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
  • 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: GitHub Actions

  • Slurm
  • GCP
  • Azure
  • Docker
Responsibilities
  • 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 GitOps 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
Qualifications
  • 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 GitOps deployment patterns
  • Comfort operating in mixed environments: multi-cloud (AWS primary, GCP/Azure secondary) and HPC schedulers like Slurm
  • Fluency in Python and TypeScript/JavaScript; experience with React, GraphQL, and Docker
  • Mature CI/CD instincts: GitHub Actions, reproducible builds, environment parity
  • Excellent written and verbal communication skills in English
Nice to Have
  • Experience in the medical technology domain (DICOM, PACS, de-identification, or clinical trial imaging)
  • Familiarity with computer vision and machine learning applications/pipelines
  • Experience with Ray (Ray Serve, Ray Data, or Ray Train) in production
  • Experience serving deep learning models with real latency and throughput requirements
  • Familiarity with regulated environments (HIPAA, GDPR, SOC 2, or FDA-regulated software)
  • Bachelor's degree in engineering, computer science, or a related field
Agentic Engineering
About
  • Working effectively with Claude Code (or comparable agentic tooling) on large, existing codebases
  • Structuring repositories, context, and documentation so agents produce production-quality output
  • Building custom tooling — MCP servers, skills, subagents, hooks — where it earns its keep
  • Where agents should be trusted, where they should be reviewed, and how to tell the difference
  • If you've been quietly reshaping how your team works because of these tools, we want to talk to you
Benefits
  • Competitive pay and equity compensation
  • Competitive medical, vision, and dental insurance coverage
  • 4 weeks of vacation per year
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