Senior Software Developer – Machine Learning Platform
- Montréal, QC
- On-site
- Posted Jul 15, 2026
- 1 position
Opens an external site
- Employment type
- Full-time
- Experience level
- Senior · 5+ years
- Apply by
- Jan 31, 2027
- Posting language
- English
- Working hours
- 40 hours per week
- Seniority
- Mid-Senior level
Job summary
Develop and maintain a scalable AI platform that supports thousands of models and millions of daily queries. Collaborate with scientists and engineers to integrate agentic applications and improve platform reliability and observability.
Job details
Build the backbone of AI at scale Want to see your work power millions of machine learning predictions every day? Join our Machine Learning Platform team and help bring models, including Large Language Models (LLMs), into production in a reliable and scalable way. You’ll contribute to a platform that trains thousands of models and serves hundreds of millions of queries daily, while growing your expertise in distributed systems, machine learning infrastructure and agentic workflows. As a Backend Developer, you will: Contribute to the development lifecycle, including coding, testing, and deployment Analyze and help improve the ease of use, observability and reliability of our AI platform Participate in maintaining services handling millions of requests and LLM calls per day Collaborate with applied scientists, data engineers, and developers to integrate agentic applications into production Contribute to evolving our AI platform to support the growth and scale of agentic workflows for Coveo users Suggest improvements to existing processes and use AI coding tools to support your development workflow Here is what will qualify you for the role: 5+ years of experience in backend development in a cloud environment (Python or Java/Spring preferred, AWS an asset) Good understanding of distributed systems and scalable application design Ability to solve problems and debug systems with guidance when needed Comfortable learning new tools, technologies, and best practices What will make you stand out: Familiarity with Terraform, AWS Bedrock, OpenSearch serverless or other vector databases, LiteLLM or other LLM inference gateways Exposure to machine learning workflows or agentic workflows Interest in scalable backend services, large-scale realtime systems, agentic workflows and applications or realtime inference at scale You don’t need to check every single box; passion goes a long way and we appreciate that skillsets are transferable. Send us your application, we want to hear from you! Join the Coveolife! We encourage all qualified candidates to apply regardless of, for example, age, gender, disability, gaps in CV, national or ethnic background. This job description was written by humans, assisted by AI. We may leverage technology in our hiring process to help us see the person behind the resume. Coveo is committed to providing accessible employment practices. If you require accommodation due to a disability at any point during the recruitment process, please contact HR@Coveo.com to discuss your needs.
What you’ll do
Develop and maintain a scalable AI platform that supports thousands of models and millions of daily queries. Collaborate with scientists and engineers to integrate agentic applications and improve platform reliability and observability.
Requirements
Requires over 5 years of backend development experience in cloud environments, preferably with Python or Java. Candidates should have a strong understanding of distributed systems and the ability to debug complex systems.
Listed skills
- Amazon Web Services · Preferred
- Java · Preferred
- Terraform · Preferred
- Python · Preferred
Other relevant skills
Identified from the job description. Confirm important requirements above.
- Backend Development
- Python
- Java
- Spring
- AWS
- Distributed Systems
- Machine Learning Infrastructure
- LLM Inference
- Terraform
- AWS Bedrock
- OpenSearch
- Vector Databases
- LiteLLM
- Agentic Workflows
- Scalable Application Design
- Observability
Job areas
- Software
- Technology
- Engineering
- Data & Analytics
- Science & Research
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