Location: Toronto, Ontario
Our client is on a mission to power the future of customer support through the responsible and efficient deployment of GenAI bots in contact centers. Our platform transforms raw enterprise data into a secure, structured, and model-ready format, enabling companies to deploy powerful AI assistants with confidence.
They help organizations avoid the costly mistakes of feeding unclean data to LLMs — ensuring their bots don’t hallucinate or mislead customers.
The Role:
We’re looking for a Staff/Data Engineer to join as a key engineering hire. You’ll work closely with the VP of Engineering & AI to build the foundation of our data platform, shaping everything from ingestion to transformation to pipeline orchestration.
This is a hands-on, high-impact role — perfect for someone who thrives in early-stage environments and wants to take full ownership of backend/data systems from the ground up.
What You’ll Do
• Architect, build, and maintain robust and scalable data pipelines to support GenAI applications
• Own data ingestion and transformation processes, integrating data from multiple structured and unstructured sources.
• Design and implement Retrieval-Augmented Generation (RAG) systems.
• Work with vector databases, embeddings, and LLM-adjacent infrastructure.
• Collaborate with AI/ML engineers to ensure data is clean, structured, and optimized for model consumption.
• Serve as the go-to technical expert for all things data — pipelines, storage, security, and performance.
• Establish and enforce best practices for data engineering across the org.
Special Perks:
- Join a technology startup led by a 7x founder that has had successful exits
- Be part of the foundational team and build products that solve massive problems and have huge upside
- Have some skin in the game with a very aggressive equity component (along with strong base salary)
Must Have Skills:
What We’re Looking For:
• 6+ years of backend/data engineering experience, ideally in high-growth tech environments.
• Deep expertise in building and managing data pipelines (Airflow, Dagster, dbt, etc.).
• Strong Python skills (Pandas, FastAPI, PySpark).
• Experience with cloud data warehouses (Snowflake, BigQuery, Redshift) and storage systems (S3, GCS).
• Proficient with SQL and schema design.
• Hands-on experience with vector databases (e.g., Pinecone, Weaviate, FAISS).
• Familiarity with LLMs, embeddings, and building RAG pipelines.
• Strong understanding of data security and compliance best practices.
Nice to Have Skills:
Preferred Attributes
• Experience in early-stage startups (0•1 product experience a big plus).
• Highly autonomous and comfortable in ambiguous environments.
• Excellent communication skills — able to work cross-functionally with product, design, and AI/ML.
• Proven ability to simplify complex data systems and make technical decisions with clarity.
• Experience building AWS data pipelines
