Senior / Staff Software Engineer, AI Tooling
Waabi · Toronto, ON ·
- Work mode
- Hybrid
- Seniority
- Staff
- Employment
- Full time
- Category
- Software engineering
- Experience
- 5+ years
- Salary
- USD 165,000 – 265,000 / year
Waabi · Toronto, ON ·
Waabi (autonomous trucks and robotaxis) is hiring a Senior/Staff engineer for a new AI Tech Strike Team that builds internal AI tooling, agents, and workflows — integrating tools like Claude Code, Cursor, and Copilot, evaluating models, adding observability and guardrails, and driving adoption across engineering and business teams. Core stack: Python, CI/CD, and LLM-based agents.
The latest advances in AI tooling is fundamentally changing all teams' ways of working - from ML model development, to traditional software development, to non-technical business functions. We are building a dedicated AI Technical Strike Team to establish centralized best practices for working with AI across Waabi with the aim of maximizing productivity. We are looking for hands-on senior software engineers to build the AI tooling, agents, and workflows that accelerate how we work. As a Software Engineer on the AI Tech Strike Team, you will design, build, and ship the tools that compound the productivity of every team at Waabi. The team will own a mix of core tooling work and deployed engagements, where members of the team work closely with functions across Waabi to understand their pain points and co-design AI workflows to maximize productivity.
Design, build, and ship custom internal tooling, agents, and workflows tailored to Waabi — supporting our autonomy codebase, simulation environments, ML training pipelines, and research workflows, as well as agents and automations for business teams.
Integrate and extend third-party AI tools — from coding assistants and agents (e.g., Claude Code, Cursor, GitHub Copilot) to AI tools for non-engineering functions — building the integrations, configurations, and internal extensions that make them work well for Waabi.
Evaluate new AI tools, models, and agent frameworks as they emerge, run structured pilots, and provide clear technical recommendations that inform build-vs-buy decisions.
Partner directly with engineers, researchers, and business teams to understand their workflows, prototype solutions quickly, and iterate based on real usage.
Build observability around AI tooling at Waabi — tracking usage, adoption, cost, and quality — so we can prioritize with data and understand impact.
Implement the guardrails for responsible AI tooling at Waabi in partnership with Security, Legal, IT, and Infrastructure.
Drive adoption of the tools you build through documentation, enablement, office hours, and hands-on support — helping every team get more out of their tools every week.
5+ years of software engineering experience, with a track record of shipping tools, platforms, or products used by large internal or external user bases.
Deep, hands-on familiarity with the current generation of AI coding tools and agents (Claude Code, Cursor, Copilot, Codex, or similar), and demonstrated experience building and shipping AI-powered products, agents, or workflows — including prompt engineering, evals, tool use, and integrating LLMs into production systems.
Strong proficiency in Python (or another common programming language), and comfort working across modern build systems, CI/CD pipelines, and developer infrastructure.
Strong product instincts and judgment: you can identify high-leverage problems across a diverse set of teams, scope pragmatic solutions, and ship things that actually get adopted.
Strong written and verbal communication skills, comfortable operating with a high degree of autonomy in ambiguous, fast-moving territory and influencing engineers, researchers, and business partners.
Passionate about self-driving technologies, frontier AI, and using AI to push the boundary of what a small, world-class team can accomplish.
Prior experience in a developer productivity, platform engineering, or AI tooling role, ideally with exposure to ML, robotics, or autonomous systems infrastructure (e.g., training pipelines, simulation tooling, large monorepos).
Experience working effectively with non-engineering stakeholders — translating business workflows into technical solutions for functions like Finance, Commercial, Marketing, HR, Legal, and Operations.
Experience building AI workflows or automation for business functions outside of engineering (e.g., finance automation, marketing operations, HR workflows).
Experience deploying and operating AI systems in security- and IP-sensitive environments.
Contributions to open-source AI tooling, agent frameworks, or developer tools.