Senior Azure GenAI Backend Engineer- Remote (RAG & Serverless Focus) (PL861)

Overview

Engagement Type:6 Months contract(can be extended)
Location: Remote

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

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Design and implement RAG-based architectures using Azure OpenAI and Azure AI Search.

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Develop backend APIs and services to support GenAI applications.

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Architect and deploy Azure serverless solutions (Azure Functions, Logic Apps, Container Apps).

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

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

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

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Apply infrastructure as code using Terraform or Bicep.

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

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Enforce security, governance, and compliance best practices.

Requirements
Required Skills & Experience
Core GenAI & Architecture

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Hands-on experience building RAG solutions in production.

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Strong understanding of LLMs, embeddings, vector search, prompt engineering.

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Experience with Azure AI Search and Azure OpenAI.

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Knowledge of agentic workflows (preferred).

Azure & Cloud

- Strong experience with:

- Azure Functions

- Azure Container Apps

- Azure App Services

- Azure Storage & Key Vault

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Solid understanding of Azure networking & identity management.

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Experience designing serverless architectures.

Backend Development

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Strong proficiency in Python, Java or .

- REST API development and microservices.

- Strong system design capabilities.

DevOps

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

- Docker & Kubernetes (good to have).

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Infrastructure as Code (Terraform / Bicep).

Nice to Have

- AWS exposure.

- Consulting experience.

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Experience deploying AI systems in regulated environments.

Originally posted on Himalayas