Why This Job is Featured on The SaaS Jobs
AI features in SaaS increasingly depend on dependable, near real time inference infrastructure, and this role sits directly in that layer. The focus on uptime, distributed systems, and event driven components reflects a product environment where machine learning is operationalised as a platform capability rather than a one off model deployment. For SaaS engineers, that intersection of ML and production reliability is becoming a defining competency.
Long term, the work builds experience that transfers across modern SaaS organisations: running customer facing systems on Kubernetes, deploying frequently with CI/CD, and designing for observability and fault tolerance. Close collaboration with Data Science also develops practical fluency in turning research outputs into maintainable services, a common gap in AI product teams. Exposure to multiple languages alongside asynchronous Python reinforces a systems mindset over framework specific expertise.
This role tends to suit engineers who like owning foundational services and improving them iteratively through measurement and operational feedback. It also fits professionals who prefer collaborative engineering practices such as PR reviews and RFCs, and who value learning by working across infrastructure, data pipelines, and product facing performance constraints.
The section above is editorial commentary from The SaaS Jobs, provided to help SaaS professionals understand the role in a broader industry context.
Job Description
Your role
As a Software Engineer–AI Core, you’ll take key ownership of the development and uptime of Dialpad’s proprietary near real-time ML inference system, a large-scale distributed system built by leveraging technologies like Kubernetes, Redis, event-driven message bus systems, modern asynchronous Python, and a plethora of open-source technologies. You’ll contribute directly to powering Dialpad’s AI products at scale, working closely alongside the Data Science teams to unleash AI features that work for our customers.
This position reports to our Engineering Manager, AI Engineering, and has the opportunity to be based in our Kitchener, Canada office.
What you’ll do
- You’ll acclimate and be paired directly with a peer (in addition to your manager) whose job it will be to make sure you have the information and tools you need to be successful.
- You’ll work primarily with fully asynchronous modern Python, but we are strong believers in using the right tool for the job, making use of Java, C++, and Golang in our stack.
- You’ll be exposed to open-source software. We employ many open-source technologies to get the job done, and we love to contribute back to those communities. We also maintain open-source codebases for libraries we’ve created ourselves.
- You’ll collaborate. All levels of engineers on the team participate in authoring and reviewing PRs for code changes and RFCs for more major system changes.
- You’ll have the opportunity to deploy code daily on Google Cloud Platform using modern best practices like Kubernetes, Docker, and CI/CD systems.
- You’ll work with the team to continuously learn by constantly evaluating and applying state-of-the-art systems and techniques to ensure we build systems that are fault-tolerant and highly scalable.
- You’ll build and manage high-performance real-time data pipelines, taking significant ownership of key components of the stack.
- You’ll share. Exploring knowledge and findings with teammates is highly encouraged, with weekly opportunities to host or attend learning sessions including members of both Engineering and Data Science teams.
Skills you’ll bring
- You have a Bachelor’s Degree in Computer Science, Mathematics, Software Engineering, or a related field, or equivalent work experience.
- You have strong fundamentals in software engineering and computer science.
- You’re excited to work on a distributed team; you value collaboration whether your teammate sits beside you or across an entire continent.
- You have strong experience working with one or more dynamically typed programming languages.
- You have a strong desire to continuously learn.
- You enjoy efficient evaluation of a problem space and finding the right tool for the job.
- You measure & monitor everything, ensuring stability, redundancy, and runtime.
- You make data-driven decisions - Measure twice, cut once.
- You enjoy learning from your experiences and sharing your knowledge with your team.
- You work on diverse problems across different systems.
- You appreciate code and system maintainability and support continuous improvement.
- Fluency in English.
Bonus points
- The Python ecosystem.
- Cloud providers such as Google Cloud Platform or AWS.
- Git or other version control systems.
- Relational and/or non-relational database systems, Pub/Sub, Messaging Systems.
- Building and managing batch or streaming data processing pipelines, ETLs.
