Senior Gen AI Engineer – RAG, Agents & AWS

Tiger Analytics Inc.; Toronto; On-site; CAD 120,000 - 160,000; Full time

Job summary

Tiger Analytics is seeking a highly skilled AI Engineer in Toronto to build high-performance API services and GenAI architectures with 7+ years of software experience.

You will design RAG pipelines, integrate AWS Bedrock and other LLM providers, optimize latency, and manage agented AI orchestration in a DevOps-friendly AWS stack.

Expect to work on retrieval models, vector stores, and evaluation frameworks, with career growth in a small, fast-growing, entrepreneurial team.

Qualifications

• Minimum of 7+ years of professional experience in software development and AI engineering.
• Hands-on experience integrating Generative AI/LLM APIs, AWS Bedrock, and other model providers.
• Experience with DevOps, CI/CD pipelines, and ML pipelines within the AWS ecosystem.
• Exposure to building Gen AI/Agentic AI applications and managing backend infrastructure.
• Strong Python skills with OpenAI API standards, JSON RESTful design, and LLM orchestration.
• Experience with Bedrock Agent/Core services is a plus.

Responsibilities

• Design end-to-end RAG pipelines with retrievers and vector stores and generators.
• Develop autonomous or semi-autonomous agents and manage tool integration and error handling.
• Evaluate performance with RAGAS or TruLens and iterate improvements.

Skills

Python

OpenAI API

JSON REST

LLM orchestration

Latency optimization

RAG pipelines

AWS Bedrock

DevOps CI/CD

Agentic AI

LangChain familiarity

Tools

Pinecone

Weaviate

pgvector

LangChain

CrewAI

Semantic Kernel

AWS Bedrock

Job description

Tiger Analytics is seeking a highly skilled AI Engineer in Toronto to build high-performance API services and GenAI architectures with 7+ years of software experience.

You will design RAG pipelines, integrate AWS Bedrock and other LLM providers, optimize latency, and manage agented AI orchestration in a DevOps-friendly AWS stack.

Expect to work on retrieval models, vector stores, and evaluation frameworks, with career growth in a small, fast-growing, entrepreneurial team.