Senior Backend Engineer

DataRobot•Oakville, ON

66d

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. As a Senior Software Engineer focused on agent and application builder experience, you will design and build systems that shape how customers create, configure, orchestrate, and monitor AI-powered applications on the DataRobot platform. Your work will improve usability, reliability, and transparency of agent workflows and application lifecycle management, ensuring customers can move from idea to production quickly and safely. You will work closely with Product, UX, Platform, and AI/ML teams to turn customer feedback into intuitive platform capabilities that make AI applications easier to manage, debug, scale, and trust in production.

Requirements

5+ years of backend software engineering experience building customer-facing applications or developer tools.
Strong experience designing APIs and service contracts that prioritize usability, clarity, and long-term maintainability.
Proficiency in at least one backend language (Python, Java, Go, C++, or similar).
Working knowledge of frontend integration concepts (component-based architectures, state management, API consumption).
Solid understanding of observability for complex workflows (logs, metrics, tracing, error reporting, and debugging tooling).
Ability to reason about customer needs, navigate ambiguity, and balance performance, usability, and reliability.
Experience with one or more cloud platforms (AWS, GCP, Azure).

Nice To Haves

Experience improving developer experience or platform usability for internal or external customers.
Familiarity with GenAI / LLM-based systems, including agent workflows, tool calling, or prompt-driven execution.
Background in application lifecycle management, deployment pipelines, or runtime configuration systems.
Exposure to enterprise environments, including regulated, hybrid, or on-prem deployments.

Responsibilities

Improve the end-to-end experience for building, deploying, and operating AI applications, from configuration and execution to monitoring and troubleshooting.
Develop MCP-compatible tool frameworks that enable secure, observable, and reusable integrations between agents, data sources, UI components, and services.
Build systems that provide clear visibility into agent and tool behavior, including status, logs, metrics, traces, and tool-call diagnostics.
Collaborate with Product and UX to turn customer pain points into platform enhancements that reduce complexity.
Balance flexibility and extensibility with simplicity, ensuring new capabilities improve the customer experience.
Participate in architectural discussions around application framework, extensibility, and long-term evolution.
Mentor junior engineers and contribute to best practices around API design, developer experience, and customer-facing reliability.