Artificial Intelligence Engineer

Senior AI-Native Software Engineer

Type: Full-time employee

Location: Toronto, ON (Hybrid)

Team: Technology / Engineering

Level: Senior

Description

Our client is a leading high-scale digital marketplace in Canada that enables millions of consumers to connect, trade, and transact locally and sustainably. Spanning hundreds of categories across goods, services, and digital listings, community engagement is at the core of their business. They innovate through data-driven experimentation and leverage extensive market experience to shape community-driven commerce and foster financial accessibility.

The organization is currently undergoing a complete platform modernization to enhance user experience and streamlines tools for both buyers and sellers.

The company is backed by a global leader in online marketplaces and classifieds platforms operating across multiple international markets.

About the Team

The Product and Technology team operates one of the largest e-commerce platforms in the country. They are transitioning from AI-assisted coding to AI-native software engineering - where autonomous agents manage an increasing share of end-to-end delivery from ideation to user-facing impact, and engineers design, supervise, and continually optimize agentic workflows.

The engineering culture values driven, inventive, and collaborative individuals who thrive in an autonomous, high-impact environment.

The Role

As a Senior AI-Native Software Engineer, you will build the agentic development pipelines that transform how software is delivered across the platform. This role goes far beyond Copilot-style code autocompletion. You will design, orchestrate, and operate end-to-end workflows where agents take requirements from issue tracking systems (e.g., Jira or Linear) through specification, implementation, testing, code review, and production deployment, incorporating appropriate human-in-the-loop checkpoints.

You will own your initiatives end-to-end - from initial concept to post-production monitoring. You will identify high-leverage opportunities, partner with internal end-users to shape solutions, ship code, and measure performance in production. The team is looking for a curious, product-minded engineer who operates independently, makes sound trade-off decisions, and measures success by business outcomes rather than code volume.

This role is language-agnostic; primary emphasis is placed on how you design and build with AI rather than specific programming language mastery.

Responsibilities

• Own technical initiatives end-to-end: identify opportunities, define problems, design and build solutions, deploy to production, and continuously monitor/improve performance.
• Design, build, and operate agentic development pipelines that convert product requirements into production-ready, fully tested, and reviewed code.
• Practice and champion spec-driven development: convert product requirements from Jira or Linear into clear, machine-actionable specifications and automated developer workflows.
• Orchestrate multi-agent systems and long-running workflows using engines like Temporal, ensuring resilient handling of state, retries, failure modes, and human-in-the-loop approvals.
• Instrument developer pipelines with observability and tracing tooling such as LangFuse to monitor agent behavior, token spend, latency, and output quality.
• Define clear success metrics up front and evaluate whether automated workflows deliver tangible value to software engineers, product teams, and end users.
• Integrate and extend advanced LLM tooling (e.g., Claude Code, Codex, and multi-model gateways), selecting optimal models and tools for specific development tasks.
• Build evaluation harnesses, guardrails, and quality gates to guarantee agent-generated code is reliable, secure, and maintainable.
• Manage LLM token usage and compute costs deliberately, balancing budget, speed, and output quality.
• Partner with engineering teams across the enterprise to drive adoption of agentic workflows, documenting patterns, playbooks, and best practices.
• Execute technical experiments, stay current with AI engineering developments, and incorporate modern methodologies into internal software practices.
• Ensure overall code quality by auditing agent outputs, resolving technical debt, and improving build, CI/CD, and testing infrastructures.

What We Are Looking For

• Senior-level software engineering background with a proven track record of shipping and operating complex production systems.
• Hands-on experience building end-to-end agentic development workflows beyond basic AI pair-programming assistants (ability to demonstrate pipelines designed, executed, and refined).
• Demonstrated ownership of software projects from concept through post-production observability and operational health.
• Strong product mindset: starting with the core user problem, weighing trade-offs by business value, and executing pragmatically.
• High degree of self-direction and autonomy in navigating ambiguous problems without requiring granular specification.
• Deep curiosity around AI technology and continuous experimentation with evolving LLM developer tooling.
• Grounding in spec-driven development and converting high-level product requirements into precise, machine-actionable specs.
• Experience orchestrating workflow automation engines (e.g., Temporal or equivalent workflow platforms).
• Familiarity with LLM observability, evaluation platforms, and tracing frameworks (e.g., LangFuse).
• Proficiency with developer AI tools (e.g., Claude Code, Codex) and multi-model routing architectures.
• Strong core engineering fundamentals: distributed systems, error/failure handling, system design, testing, and security principles.
• Familiarity with CI/CD platforms (e.g., GitHub Actions) and major cloud providers (GCP, AWS).
• Comfort working across full-stack architectures and adapting quickly to unfamiliar codebases and languages.
• Excellent communication skills with the ability to articulate, teach, and mentor teams on AI-native engineering practices.
• Experience with prompt/context engineering, MCP (Model Context Protocol) servers, and custom tool-use design.
• Ability to construct evaluation frameworks and regression testing suites for non-deterministic LLM systems.

Nice to Have

• Experience building consumer-facing applications, ideally within high-volume digital marketplaces, e-commerce platforms, or high-traffic web platforms.

Core Cultural Values

• Be ambitious and challenge traditional engineering paradigms.
• Remain curious and continuously learn as tools evolve.
• Stay laser-focused on user value and business outcomes.
• Maintain complete end-to-end ownership from idea to production.
• Collaborate cross-functionally and iterate rapidly.

This Role Is NOT For You If:

• You require fully specified technical tickets where your role is purely executing code to spec. In this role, you define the problem and write the specifications yourself.
• You expect to hand off testing, QA, and operational monitoring to separate teams. In this role, you own quality, reliability, and production performance directly.

Why Join This Organization

• Lead the AI-native developer transformation for a premier Canadian digital property operating at massive consumer scale.
• Experience real autonomy, executive trust, and complete ownership over system architecture and team workflows.
• Collaborate with international sister platforms across a global digital marketplace group on shared tooling and best practices.
• Join a culture rooted in continuous learning, mentorship, experimentation, and high impact.