Developer - AI​/ML

Meet Benevity

Benevity is the way the world does good, providing companies (and their employees) with technology to take social action on the issues they care about. Through giving, volunteering, grantmaking, employee resource groups and micro-actions, we help most of the Fortune 100 brands build better cultures and use their power for good. We’re also one of the first B Corporations in Canada, meaning we’re as committed to purpose as we are to profits.

We have people working all over the world, including Canada, Spain, Switzerland, the United Kingdom, the United States and more!

Benevity’s software architecture has evolved to include a diverse technology stack. The front‑end application, using mainly VueJS, is designed for both desktop and mobile web rendering. Our back‑end systems (some Java Spring Boot, some PHP) manage data processing, interfaces with external providers, and ensures robust security. We run and operate our systems in both GCP and AWS cloud, leveraging where possible cloud‑native technology.

We emphasize clean, maintainable code and use GIT for version control and collaboration. Additionally, our platform integrates with various external services for functionalities like email communication, content storage, and server‑to‑server interactions.

Our culture is driven by our core value of “we‑are‑we” and as a Staff Developer AI/ML, you will work in an outcome‑driven environment where collaboration with your product, design and engineering counterparts is paramount.

If you’re eager to make a difference and thrive in a collaborative setting, we invite you to join our team!

The Staff AI/ML Engineer will be the technical anchor for our machine learning and AI efforts, and will lead the architecture of our GenAI strategy. You will bridge the gap between theoretical research and production‑grade engineering. This role requires a deep understanding of designing scalable systems that powers our model training, deployment, and monitoring — ensuring our AI initiatives deliver measurable business value.

The ideal candidate will have a strong technical background combined with leadership experience.

• Design and oversee the development of robust end‑to‑end ML architecture, from data ingestion and feature stores to model serving and monitoring.
• Define the long‑term roadmap strategy for our AI infrastructure and orchestration framework.
• Oversee the design, implementation, and maintenance of our AI/ML ecosystem.
• Set the standard for MLOps — you will ensure that our ML ecosystem is as testable, maintainable, and scalable as our core application code.
• Cross‑functional leadership — by working closely with Product Managers, Data Scientists and ML Engineers to translate business problems into concrete technical requirements.
• Act as a force multiplier for the team by conducting high‑level design reviews and mentoring engineers on system design and performance optimization.
• Architect and evolve LLM‑powered applications (e.g., copilots, search, assistants, agents), including RAG pipelines, tool integrations, and multi‑step reasoning workflows.
• Design and implement robust evaluation frameworks for GenAI systems, incorporating offline benchmarks, online metrics, and human‑in‑the‑loop feedback.
• Drive best practices for prompt engineering, agent design, and orchestration frameworks, ensuring maintainability and performance at scale.
• Establish guardrails and safety mechanisms for GenAI applications, including prompt injection defenses, hallucination mitigation, and responsible AI practices.
• Establish the golden path for model versioning, A/B testing, and automated rollbacks for identifying and mitigating drifts.
• Ensure AI architectural strategy aligns with industry best practices and standards, complies with security policies and industry regulations.
• Identify opportunities for process improvements and implement solutions to enhance platform performance and efficiency.

• Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related field, or equivalent deep professional experience.
• 7+ years of software engineering experience, with at least 4+ years architecting and deploying ML…