Senior AI Engineer with GenAI/LLM

Mississauga, Ontario, CanadaHybridFull TimeSeniorPosted 2 months ago

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Role summary

We are seeking a Senior AI Engineer with expertise in Generative AI and Large Language Models (LLMs) to build and deploy enterprise-grade AI solutions. The role focuses on RAG pipelines, prompt engineering, and production-ready systems. Responsibilities include designing, developing, and deploying LLM applications, optimizing RAG, implementing prompt strategies, developing agentic frameworks, integrating GenAI with enterprise systems, and utilizing vector databases. The engineer will deploy scalable solutions using MLOps and CI/CD, and work with cloud-native technologies like Kubernetes. A strong foundation in ML, NLP, Python, and experience with relevant AI platforms and tools are essential.

Senior AI Engineer (GenAI/LLM)

Location: Mississauga, Canada (Hybrid)

Experience: 8–10 Years

About the Role

We are looking for highly skilled Service AI Engineers with strong expertise in Generative AI and Large Language Models (LLMs). This role involves building, deploying, and scaling enterprise-grade AI solutions with a focus on RAG pipelines, prompt engineering, and production-ready AI systems.

Key Responsibilities

Design, develop, and deploy LLM-based applications in enterprise environments

Build and optimize Retrieval-Augmented Generation (RAG) pipelines

Implement advanced prompt engineering strategies and reusable templates

Develop AI-powered solutions using agentic frameworks

Integrate GenAI capabilities with enterprise systems using APIs and orchestration tools

Work with vector databases for efficient data retrieval and storage

Deploy scalable solutions using MLOps and CI/CD pipelines

Collaborate with cross-functional teams to solve complex AI challenges

Core Requirements

AI/ML & GenAI Expertise

Strong foundation in Machine Learning, NLP, Neural Networks, and LLMs

Hands-on experience with models like OpenAI, Google Gemini, Claude, Llama, Mistral

Deep understanding of RAG architecture and implementation

Experience with platforms like Vertex AI, Hugging Face

Knowledge of Guardrails & AI safety evaluation techniques

Programming & Data Engineering

Strong proficiency in Python (Must Have) (Java acceptable if willing to work in Python)

Experience with libraries/tools:

Pandas, NumPy, scikit-learn

PyTorch, TensorFlow

Transformers, LangChain, LlamaIndex

FastAPI, Seaborn

Experience working with unstructured data at scale

Hands-on with vector DBs: Pinecone, MongoDB Atlas, PGVector, Neo4j

Deployment & MLOps

Experience deploying GenAI models to production

Strong understanding of MLOps, model evaluation, and pipelines

Experience with CI/CD tools: Jenkins, GitLab CI, Azure DevOps, ArgoCD

Cloud & DevOps

Experience with Kubernetes / OpenShift

Knowledge of containerized, cloud-native deployments

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