Design, develop, and deploy Generative AI solutions, including LLM-based applications, agents, and automation workflows.
Build and maintain APIs, microservices, and backend components for integrating AI into production systems.
Perform prompt engineering, fine-tuning, RAG pipelines, vector databases, and model optimization.
Collaborate with data engineering teams to prepare, process, and manage training datasets.
Implement secure, scalable, and high‑performance architectures for AI workloads on cloud platforms (AWS/Azure/GCP).
Monitor AI model performance, bias, drift, and reliability; implement continuous improvements.
Ensure compliance with organizational security, governance, and responsible AI standards.

Requirements

Hands‑on experience with LLMs, Generative AI frameworks, or similar ML/AI technologies
Proficiency in Python, API development, and backend engineering
Experience with Vector databases (Pinecone, FAISS, Chroma, Elasticsearch)
Knowledge of RAG, embeddings, fine‑tuning, and prompt optimization techniques
Familiarity with ML frameworks such as PyTorch or TensorFlow
Experience deploying scalable AI solutions on AWS/Azure/GCP
Strong understanding of data pipelines, model lifecycle, and MLOps

Benefits

Paid time off based on employee grade (A-F), defined by policy: Vacation: 12-25 days, depending on grade
Company paid holidays
Personal Days
Sick Leave
Medical, dental, and vision coverage (or provincial healthcare coordination in Canada)
Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada)
Life and disability insurance
Employee assistance programs
Other benefits as provided by local policy and eligibility

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

Generative AILLMsPythonAPI developmentbackend engineeringVector databasesRAGMLOpsPyTorchTensorFlow