Back End Developer (AI Infrastructure)

Montreal, Quebec, Canada
Remote
Posted Oct 7, 2026
1 position

US$20–US$100 / hour

Opens LinkedIn

Employment type: Contract
Experience level: Entry, Junior · 0+ years
Posting language: English
Working hours: 40 hours per week
Location requirements: Country, Montreal, Quebec, Canada
Seniority: Entry level

Job summary

Design, build, and maintain back-end services, APIs, data pipelines, and scalable infrastructure supporting AI training and inference workloads. Improve performance and reliability, troubleshoot production issues, review code, and collaborate asynchronously on technical and architectural decisions.

Job details

About The Role What if the code you write could directly power the AI systems shaping how millions of people interact with technology? We're looking for Back End Developers to design, build, and optimize the server-side systems and APIs that drive cutting-edge AI products — from data pipelines and model-serving infrastructure to scalable microservices that handle real-world traffic at scale. This is a fully remote, flexible contract role open to engineers in Montreal and across Canada. Whether you're a seasoned engineer looking for meaningful project work or a strong developer ready to apply your skills to AI-adjacent infrastructure, this is your chance to build things that matter. Organization: Alignerr Type: Hourly Contract Location: Remote Commitment: 10–40 hours/week What You'll Do Design, develop, and maintain robust back end services, APIs, and data pipelines Build scalable, high-performance server-side architecture to support AI training and inference workloads Write clean, well-documented, and testable code following engineering best practices Integrate with databases, message queues, cloud services, and third-party APIs Optimize system performance, reliability, and scalability as usage grows Collaborate asynchronously with distributed teams of engineers, researchers, and product leads Troubleshoot production issues, conduct code reviews, and contribute to architectural decisions Work independently on task-based and project-based assignments on your own schedule Who You Are Proficient in one or more back end languages — Python, Go, Java, Node.js, Rust, or similar Solid understanding of RESTful API design, microservices architecture, and distributed systems Experienced with relational and/or NoSQL databases (PostgreSQL, MongoDB, Redis, etc.) Comfortable working with cloud platforms such as AWS, GCP, or Azure Familiar with version control (Git), CI/CD pipelines, and containerization (Docker, Kubernetes) Strong problem-solving skills and the ability to debug complex systems independently Self-motivated, reliable, and effective when working asynchronously without close supervision Clear communicator who can document decisions and collaborate across time zones Nice to Have Experience building infrastructure for machine learning or AI systems Familiarity with data processing frameworks (Apache Kafka, Spark, Airflow, or similar) Background in performance optimization, caching strategies, or high-throughput systems Knowledge of authentication, authorization, and security best practices Experience with serverless architectures or event-driven design patterns Contributions to open-source projects or a strong portfolio of personal/professional work Why Join Us Work on cutting-edge AI infrastructure projects alongside leading research labs Fully remote and flexible — set your own hours and work from anywhere Freelance autonomy with access to meaningful, technically challenging work Build systems at the intersection of software engineering and artificial intelligence Collaborate with a global network of talented engineers and researchers Potential for ongoing work and contract extension as new projects launch

What you’ll do

Requirements

Candidates should be proficient in one or more back-end programming languages and have experience with APIs, microservices, distributed systems, databases, and cloud platforms. They should also be comfortable with Git, CI/CD, and containerization, and be able to solve problems independently, communicate clearly, and work asynchronously.