Design, build, and deploy AI-powered product features across Canals’ core workflows.
Develop and maintain LLM-powered systems, including agents, retrieval pipelines (RAG), and workflow automation.
Build machine learning models for operational use cases such as classification, forecasting, anomaly detection, and recommendation systems.
Own the full lifecycle of ML systems: data pipelines, experimentation, training, evaluation, deployment, and production monitoring.
Work closely with product, operations, and customer teams to identify high-impact AI opportunities.
Improve the scalability, reliability, and performance of AI infrastructure and inference systems.
Establish best practices for prompt engineering, model evaluation, observability, and cost optimization.
Collaborate with backend engineers to integrate AI systems deeply into product workflows.
Help shape Canals’ long-term AI strategy as we expand automation across the platform.
Requirements
4+ years of software engineering experience, with significant exposure to machine learning or applied AI.
Strong backend engineering fundamentals and experience building scalable production systems.
Hands-on experience shipping ML or LLM-powered products into production.
Experience with Python and modern ML frameworks such as PyTorch, TensorFlow, or Scikit-learn.
Experience working with LLM APIs and tooling (OpenAI, Anthropic, LangChain, LlamaIndex, or similar).
Familiarity with vector databases, retrieval systems, and AI orchestration frameworks.
Experience designing evaluation frameworks for AI quality, reliability, and performance.
Strong understanding of API design, distributed systems, and cloud infrastructure.
Ability to operate independently, move quickly, and take ownership in a product-driven environment.
Strong product intuition and the ability to translate ambiguous business problems into technical solutions.
Tech Stack
Cloud
Distributed Systems
Python
PyTorch
Scikit-Learn
Tensorflow
Benefits
We care deeply about building great products, hiring exceptional people, and creating an environment where talented individuals can do the best work of their careers.