Role Overview

We are seeking a skilled Gen AI RAG Engineer to design and develop cutting-edge Generative AI applications. This role involves implementing complex GenAI workflows, building robust backend services integrated with Azure components, and ensuring high-quality, scalable solutions.

Responsibilities

Design and develop GenAI-powered applications using Python (APIs, services, orchestration, integrations).
Implement GenAI workflows such as RAG, prompt engineering, and response evaluation.
Build and optimise backend services integrating with Azure components for deployment, security, and scalability.
Work with SQL to extract, transform, and validate data required for GenAI applications.
Create reusable components, follow clean coding practices, and maintain robust version control using Git.
Collaborate with product, data, and engineering teams to convert requirements into technical solutions.
Ensure application quality through unit tests, error handling, observability, and performance optimisation.
Communicate progress, risks, and design decisions clearly to both technical and non-technical stakeholders.

Requirements

Must-Have Skills (Required)

Python (Advanced): Strong programming fundamentals, API development, and modular design.
Generative AI: Experience working with LLMs, prompt engineering, and GenAI application patterns.
Azure: Hands-on exposure to Azure services such as App Services/Functions, Storage, Key Vault.
SQL: Strong query writing, joins, aggregations, and performance tuning basics.
Git: Branching strategies, PR reviews, conflict resolution, and collaboration workflows.
Communication: Strong verbal and written communication capabilities.
Experience with LLM application frameworks (LangChain / Semantic Kernel) and vector search concepts.
Familiarity with Azure OpenAI or similar enterprise-grade GenAI deployment practices.
Exposure to CI/CD pipelines, code quality checks, and basic cloud monitoring.
Experience building secure solutions (secrets management, RBAC, secure endpoints).