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 Staff Software Engineer in our AI Compute team, you’ll be a technical expert and a force multiplier. You’ll lead by example—rolling up your sleeves as a technical contributor to solve complex problems, shaping architecture, and mentoring engineers to do their best work and advance their careers. You’ll work across our control plane systems, influence cross-team roadmaps, and bring pragmatic engineering practices into how we build, test, and operate infrastructure software.

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.

Key Responsibilities





Build a system that ensures micro-services are secure, performant, reliable, and can go from idea to production in an hour.

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

Knowledge, Skills and Abilities

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.

Experience setting technical direction, making architectural decisions, and driving consensus across multiple teams and stakeholders

Able to influence others in the organization even where they lack explicit authority

Proven track record for leading large-scale projects to completion across dozens of teams/Pods

Experience mentoring senior engineers, fostering a positive team culture, and promoting continuous learning and improvement among colleagues

Operational excellency to continuously define and improve SLA (Service Level Agreement) working backward from customer experience for all the software components this team manages.

Requisite Education and Experience / Minimum Qualifications

8+ years of experience

Expert in developing a wide variety of software with Python (5+ 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

Preferred:

Golang, Terraform and Terragrunt

Chronosphere

Multi-cloud experience (AWS, Azure, GCP, and OpenShift)

Nice to Have

Direct experience with up-to-date 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 exper

📌 Staff Software Engineer (Toronto)
🏢 DataRobot
📍 Toronto