Senior Consultant – Azure GenAI Backend Engineer (RAG & Serverless Focus) (PL795)

Duration:

6-12 months contract (with the possibility of extension)

Work Model:

Remote, Canada

Our client in the consulting space is seeking a

Senior Consultant – Azure GenAI Backend Engineer

to design and implement scalable Generative AI solutions with a strong focus on

RAG architectures and Azure-native serverless platforms .

This role requires deep expertise in

Azure AI services, backend system design, authentication mechanisms, and cloud-native architecture

to deliver secure, production‑grade AI systems.

Key Responsibilities

Design and implement

RAG-based architectures

using Azure OpenAI and Azure AI Search.

Develop backend APIs and services to support GenAI applications.

Architect and deploy

Azure serverless solutions

(Azure Functions, Logic Apps, Container Apps).

Build scalable data pipelines for indexing, embedding, and retrieval workflows.

Implement CI/CD pipelines for AI systems using Azure DevOps or GitHub Actions.

Define and implement system architecture ensuring performance, scalability, and high availability.

Apply infrastructure as code using Terraform or Bicep.

Collaborate with frontend, data, and AI teams to deliver end-to-end GenAI solutions.

Enforce security, governance, and compliance best practices.

Core GenAI & Architecture

Hands‑on experience building

RAG solutions

in production.

Strong understanding of

LLMs, embeddings, vector search, prompt engineering .

Experience with

Azure AI Search

and Azure OpenAI.

Knowledge of

agentic workflows

(preferred).

Azure & Cloud

Strong experience with:

Azure Functions

Azure Container Apps

Azure App Services

Azure Storage & Key Vault

Solid understanding of Azure networking & identity management.

Experience designing serverless architectures.

Backend Development

Strong proficiency in Python, Java or node.js.

REST API development and microservices.

Strong system design capabilities.

DevOps

CI/CD pipelines (Azure DevOps / GitHub Actions).

Docker & Kubernetes (good to have).

Infrastructure as Code (Terraform / Bicep).

Nice to Have

AWS exposure.

Consulting experience.

Experience deploying AI systems in regulated environments.

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