about 2 hours ago
Responsibilities
- Architect and deliver production LLM-powered capabilities.
- Own prompt engineering strategy and establish team standards.
- Lead the selection and integration of embedding models and hybrid retrieval architectures.
- Define and implement LLM evaluation frameworks and quality benchmarks.
- Lead the architecture and implementation of production agentic systems.
- Design human-in-the-loop mechanisms and approval workflows.
- Write production-quality, modular, and well-tested code.
- Define and champion LLMOps practices.
- Serve as the primary technical partner for cross-functional teams.
- Mentor and grow junior and mid-level engineers.
Requirements
- Bachelor’s or Master’s degree in Computer Science, Engineering, or equivalent experience.
- 5+ years of experience building and deploying production AI/ML systems.
- Strong proficiency in Python and software engineering fundamentals.
- Deep hands-on experience with LLM APIs and advanced prompt engineering.
- Proven experience designing and deploying production RAG systems.
- Hands-on experience with agentic frameworks and multi-step agent workflows.
- Experience with cloud platforms and containerized deployment.
- Strong communication and collaboration skills.
- Track record of mentoring engineers.
Benefits
- Medical Insurance
- Dental Insurance
- Vision Insurance
- Short- & Long-Term Disability
- Life Insurance
- Flexible PTO
- RRSP with company match
Tech Stack
Categories
AI & MLData Science