About the role
Job Description
Job Title: Mid-level AI Engineer
Job Type: Full-time
Location: Canada (Remote)
Experience: 2-4 Years of Relevant Experience
Job Summary:
Join our team as a Mid-level AI Engineer and help drive the next generation of GenAI-powered applications. You will architect robust solutions, collaborating closely with fellow engineers, product managers, and designers to turn cutting-edge research into real-world impact. If you thrive in a fast-paced, innovation-driven environment and are passionate about clear communication, this is the opportunity for you.
Responsibilities:
- Build GenAI applications such as question-answering systems, content generation tools, and extraction pipelines.
- Design, implement, and optimize RAG pipelines end-to-end: ingestion, chunking, embedding, prompt templating, evaluation, and deployment.
- Develop robust APIs using Python frameworks (FastAPI preferred).
- Work with multiple LLMs (OpenAI, Mistral, Anthropic, etc.) and evaluate model performance for different use cases.
- Use LangChain, LangGraph, or LangSmith to orchestrate and monitor GenAI workflows.
- Deploy applications on AWS or Azure and implement CI/CD for continuous improvement.
- Collaborate with data engineers and product managers to translate technical designs into scalable solutions.
- Participate in system design discussions, contributing ideas for performance and maintainability.
Must-have Skills:
- Python : Strong experience with the language. Able to design clean, modular, production-grade code.
- API Development : Proven experience building and maintaining APIs (FastAPI/Flask).
- GenAI Stack : LangChain, LangGraph, LangSmith; multiple LLM APIs (OpenAI, Mistral, etc.).
- RAG Lifecycle : Data ingestion, prompt templating (Jinja), evaluation/re-ranking, deployment.
- Cloud/DevOps : Hands-on with AWS or Azure (deployments, monitoring).
Good-to-have Skills:
- Understanding of distributed systems and scaling strategies.
- Experience with containerization (Docker) and orchestration (Kubernetes).
- Familiarity with Guardrails AI or Responsible AI frameworks.
- Basic UI integration knowledge (React, optional).
Our interview process is streamlined with a single step: an AI interview. If you perform well, our hiring managers will review your AI interview recording and may extend an offer directly based on that review.
About the role
Job Description
Job Title: Mid-level AI Engineer
Job Type: Full-time
Location: Canada (Remote)
Experience: 2-4 Years of Relevant Experience
Job Summary:
Join our team as a Mid-level AI Engineer and help drive the next generation of GenAI-powered applications. You will architect robust solutions, collaborating closely with fellow engineers, product managers, and designers to turn cutting-edge research into real-world impact. If you thrive in a fast-paced, innovation-driven environment and are passionate about clear communication, this is the opportunity for you.
Responsibilities:
- Build GenAI applications such as question-answering systems, content generation tools, and extraction pipelines.
- Design, implement, and optimize RAG pipelines end-to-end: ingestion, chunking, embedding, prompt templating, evaluation, and deployment.
- Develop robust APIs using Python frameworks (FastAPI preferred).
- Work with multiple LLMs (OpenAI, Mistral, Anthropic, etc.) and evaluate model performance for different use cases.
- Use LangChain, LangGraph, or LangSmith to orchestrate and monitor GenAI workflows.
- Deploy applications on AWS or Azure and implement CI/CD for continuous improvement.
- Collaborate with data engineers and product managers to translate technical designs into scalable solutions.
- Participate in system design discussions, contributing ideas for performance and maintainability.
Must-have Skills:
- Python : Strong experience with the language. Able to design clean, modular, production-grade code.
- API Development : Proven experience building and maintaining APIs (FastAPI/Flask).
- GenAI Stack : LangChain, LangGraph, LangSmith; multiple LLM APIs (OpenAI, Mistral, etc.).
- RAG Lifecycle : Data ingestion, prompt templating (Jinja), evaluation/re-ranking, deployment.
- Cloud/DevOps : Hands-on with AWS or Azure (deployments, monitoring).
Good-to-have Skills:
- Understanding of distributed systems and scaling strategies.
- Experience with containerization (Docker) and orchestration (Kubernetes).
- Familiarity with Guardrails AI or Responsible AI frameworks.
- Basic UI integration knowledge (React, optional).
Our interview process is streamlined with a single step: an AI interview. If you perform well, our hiring managers will review your AI interview recording and may extend an offer directly based on that review.