Who You Are

You are self-driven and like to work with others to remove roadblocks. You are curious and love to explore and learn new technologies. You have demonstrated the ability to build, deploy, and maintain large-scale, complex applications. You care more about solutions and impacting the customer experience than using a particular tool or framework.

About the role:

You will join a small, highly autonomous cross-functional team to build AI agents that fundamentally transform how operations work at scale. Instead of writing bespoke software for every workflow, we are developing an agent platform that can read operational knowledge, reason about it in context, and execute tasks end-to-end. This approach allows us to scale complexity through knowledge and reasoning, rather than simply through code.

This is an opportunity to join a foundational team, which currently consists of fewer than five engineers. The work spans critical areas including LLM-powered agent design, robust backend service architecture, tool and integration development, and sophisticated knowledge infrastructure.

We are seeking a Senior Software Engineer with a strong passion for building AI-native systems in a product environment. The ideal candidate will be able to take ownership of large segments of the technology stack, make pragmatic technical decisions in ambiguous and emerging territory, and consistently ship high-quality, production-ready systems that our users rely on every day.

Responsibilities:

• Design, build, and own core components of the agent platform, from the orchestration layer to the tool integrations connecting it to internal systems.
• Build and evolve the capabilities layer: APIs, data access patterns, and service integrations for agents to execute operational workflows.
• Architect the knowledge and memory infrastructure, allowing agents to retrieve the data and act across our systems.
• Design and implement the trust and safety framework, including audit trails, human-in-the-loop controls, and guardrails for safe and auditable AI-driven operations.
• Contribute to agent evaluation and testing infrastructure, defining how we measure accuracy, reliability, and regression across agent behaviors.
• Partner directly with Operations to understand workflows, identify automation opportunities, and translate process knowledge into agent capabilities.
• Mentor other engineers on the team as it grows.

About the candidate

• You are comfortable in a fast-paced, early-stage environment. You demonstrate a "scrappy" and resourceful approach, proactively identifying solutions and unblocking yourself without needing a fully defined path.
• You are pragmatic and balance quality with speed. You understand when to optimize for long-term durability and when to iterate quickly. You prioritize pragmatism over being overly precious about code, but never compromise on quality in a way that creates future issues.
• You are product-minded. You look beyond the immediate task, seeking to understand the "why" behind the build and questioning whether it's the right product solution. You are comfortable contributing product thinking alongside engineering work.
• You demonstrate a strong ownership mindset. You are proactive, identify gaps, and drive initiatives to completion without waiting for explicit instructions. When encountering issues or ambiguity, you address them directly.
• You possess strong backend engineering fundamentals. You can confidently design, build, and operate production systems.
• You are curious and eager to develop expertise in AI and LLMs. While deep research is not required, you are motivated to build practical, real-world products using these tools, specifically focusing on agent systems.

Qualifications

• 5+ years of backend engineering experience building and operating production systems
• Hands-on experience with LLMs and AI agents (orchestration, RAG, tool/function calling, or similar)
• Strong API design and system integration skills
• Product-minded: questions requirements and contributes to product decisions, not just execution
• Proven ownership of complex projects in ambiguous, early-stage environments

Technologies Used

• Golang, Ruby on Rails, Javascript, Java, C#, Python, VueJS, MySQL, Kafka, AWS, Git, Memcache, Redis, ElasticSearch, Docker, Terraform, Kubernetes, CircleCI, DataDog

The base wage range for this position based in our Toronto office is targeted at $188,000.00 to $242,000.00 CAD per year.

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