Senior AI Developer – GenAI / LLM

Role: Senior AI Developer – GenAI / LLM

Location: Mississauga, Canada (Hybrid)

Experience: 6–10 Years

Role Overview

We are seeking experienced Senior AI Developers specializing in Generative AI and Large Language Models (LLMs). The ideal candidate will have strong hands-on expertise in building, deploying, and scaling GenAI solutions using modern AI/ML frameworks and cloud platforms.

Key Responsibilities

* Design, develop, and deploy scalable GenAI/LLM-based applications for enterprise use cases

* Build and optimize Retrieval-Augmented Generation (RAG) pipelines, including advanced implementations

* Develop robust prompt engineering strategies, prompt tuning, and reusable prompt templates

* Integrate LLMs into enterprise systems using APIs, orchestration tools, and knowledge graphs

* Work with agentic frameworks to implement intelligent, autonomous workflows

* Implement guardrails and evaluation frameworks to ensure performance, safety, and reliability of AI solutions

* Handle and process large-scale unstructured datasets efficiently

* Collaborate with cross-functional teams including product, data engineering, and DevOps

Required Skills & Qualifications

Core AI/ML Expertise

* Strong foundation in Generative AI, Machine Learning, Data Science, and Statistics

* Solid understanding of NLP, Neural Networks, and LLM architectures

LLM & GenAI Experience (Critical)

* Hands-on experience with leading LLMs such as Google Gemini, OpenAI, Anthropic Claude, Mistral, LLaMA, and open-source models

* Strong expertise in RAG pipelines (must-have)

* Experience with platforms like Vertex AI, Hugging Face

* Expertise in prompt engineering and tuning

Programming & Tools

* Strong proficiency in Python (must-have)

* Experience with libraries/frameworks:

* Pandas, NumPy, Scikit-learn

* PyTorch / TensorFlow

* Transformers, LangChain, LlamaIndex

* FastAPI, Seaborn

* Experience with vector databases:

* PGVector, Pinecone, MongoDB Atlas, Neo4j

MLOps & Deployment (Critical)

* Proven experience deploying GenAI models to production environments

* Strong knowledge of MLOps practices, model evaluation, and monitoring

* Experience with CI/CD tools:

* Jenkins, GitLab CI, Azure DevOps, ArgoCD

Cloud & Infrastructure

* Hands-on experience with Kubernetes / OpenShift

* Experience working in cloud-native environments