Senior Backend Engineer

DataRobot•Oakville, ON

31d

About The Position

DataRobot delivers AI that maximizes impact and minimizes business risk. Our platform and applications integrate into core business processes so teams can develop, deliver, and govern AI at scale. DataRobot empowers practitioners to deliver predictive and generative AI, and enables leaders to secure their AI assets. Organizations worldwide rely on DataRobot for AI that makes sense for their business — today and in the future. Our AI Compute team is the engine at the heart of DataRobot. We have a mission to build and operate the foundational computing backbone that powers all of DataRobot's AI products and our customers' most demanding workloads. This team works backwards from the needs of data scientists, ML engineers, and application developers to provide the raw power and sophisticated orchestration required to train, deploy, and manage agentic AI at any scale. We are the internal equivalent of a hyperscale cloud provider's core compute service, obsessed with performance, efficiency, and enabling the future of AI. As a Senior Backend Engineer in our AI Compute team, your primary responsibilities of this team include developing and supporting new compute primitives, designing and supporting our APIs, and instrumenting DataRobot to integrate with enterprise IT infrastructure to run Agentic workloads. Our team leverages modern technologies to achieve our goals and innovate on our solutions. This role includes participation in an on-call rotation—we believe in shared ownership of our platform and aim to build systems that are resilient, observable, and require minimal intervention.

Requirements

5+ years of experience
Expert in developing a wide variety of software with Python (4+ years)
Experience designing and operating diverse CI/CD pipelines with Harness.io
Experience designing and innovating large-scale horizontal and vertically-scaled build, testing, and deployment systems for Kubernetes environments and familiarity with Helm charts
Expert proficiency in Kubernetes architecture and operations including resource management/scheduling, auto-scaling, Gateway API/Ingress, Prometheus, and OpenTelemetry or experience with other orchestrators like nomad/slurm
Experience with gpu clusters, either as a user or administrator or experience in multi-node AI/ML
Passionate about developing products for your fellow internal developers.
Strong Computer Science fundamentals in object-oriented design, data structures, algorithm design, problem-solving, and complexity analysis.
An understanding of design for scalability, performance, and reliability.
Deep experience with automated testing and test-driven development
Demonstrable knowledge of software architecture for large systems
Real-world experience decoupling monolithic software into smaller reusable components
Self-motivated and proactive, able to take ownership and deliver results.
Ability and willingness to learn about new technologies.
Personal drive to get things finished.
Effective communication.
Operational excellency to continuously define and improve SLA (Service Level Agreement) working backward from customer experience for all the software components this team manages.

Nice To Haves

Golang, Terraform and Terragrunt
Chronosphere
Multi-cloud experience (AWS, Azure, GCP, and OpenShift)
Direct experience with modern distributed compute frameworks (e.g., Ray, Dask) and large-scale job schedulers (e.g., Slurm, Kueue).
CKAD (Certified Kubernetes Application Developer) certification
Publicly reviewable contributions to interesting development projects.
Agentic AI experience
Experience working with NVIDIA infrastructure in managing (NIM Operator, NVIDIA Dynamo Operator)

Responsibilities

Develop, test, and support features of DataRobot.
Create and maintain automated unit tests and functional tests.
Design infrastructure for new features with the input of peers.
Build a system that ensures micro-services are secure, performant, reliable, and can go from idea to production in hours.
Build a system that continuously provides recommendations to right-size computing resources for Kubernetes to ensure efficient cloud spending for ourselves and our customers.
Design and architect automated quality platforms to go from Enterprise-Grade releases from once-a-quarter to once-a-week to once-per-day to once-per-hour without sacrificing performance, security, or reliability
Work with Product, Legal and Security to ensure the continuous delivery processes you build are compliant and secure
Work with the team to ensure pipelines have clear playbooks and can operate 24/7 without you
Work with a diverse group of architects and platform engineers across our R&D department to set continuous delivery and performance requirements for all production services
Work with internal product managers to set roadmaps and define milestones to deliver innovative and simple solutions to our many teams’ continuous delivery and platform engineering issues
Manage individual projects and milestones with abundant communication of progress.