Job Description

We are seeking an exceptionally skilled Data

& AI Integration Developer

for a critical hybrid role at the intersection of database administration, full-stack development, and artificial intelligence. This position is responsible for the full lifecycle of our data--from ensuring the performance and security of our on-premise SQL

Server

environments to engineering data pipelines into Azure

and GCP

and integrating that data with AI

and Machine Learning

services.

The ideal candidate has a background in database management or full-stack development with broad skills in cloud integration, software testing, automation, and applied AI. You will build and manage integrations, develop effective prompts for generative AI, and prepare data for ML models.

Key Responsibilities:

Testing & Quality:

Write unit tests and integration tests to ensure code quality, and actively participate in troubleshooting, debugging, and resolving application defects.

DevOps:

Contribute to our CI/CD pipelines and work with cloud platforms (especially Azure) for application deployment and monitoring.

Management & Performance:

Install, configure, maintain, and tune MS SQL Server databases for high performance and availability.

Backup & Recovery:

Design, implement, and rigorously test backup and disaster recovery (DR) plans.

Security & Compliance:

Manage all aspects of database security, user access, and data masking to meet compliance standards.

T-SQL Development:

Write, test, and optimize complex stored procedures, triggers, and functions.

AI & Machine Learning:

AI Integration:

Design, build, and maintain integrations with third-party and cloud-native AI/ML services (e.g., Azure AI Services, Google Vertex AI).

Prompt Engineering:

Develop, test, and refine

prompts

for generative AI and Large Language Models (LLMs) to ensure accurate, relevant, and consistent outputs for business applications.

ML Data Preparation:

Collaborate with data scientists to prepare, cleanse, and structure datasets for ML model training and inference.

Automation:

Utilize

PowerShell

and other scripting tools to automate data preparation, model deployment pipelines, and AI service monitoring.

Integration & Business Analysis:

Cloud Integration:

Set up, manage, and monitor data pipelines between on-premise systems and cloud platforms (

Azure

and

GCP

).

Documentation:

Create and maintain detailed documentation of

data flows

, AI integrations, system architectures, and business logic.

Software Testing:

Develop test plans and perform hands-on testing for new software features, data integrations, and AI-driven functionalities.

Development Support:

Support development teams by reviewing database interaction code (primarily

.NET C#

, with exposure to

Java

and

Python

).

Required Qualifications:

[3-5+] years of experience as a Microsoft SQL Server DBA and/or Strong proficiency in C# and the .NET ecosystem. Working knowledge of

.NET (C#)

. Strong proficiency in writing and optimizing complex

T-SQL

and

stored procedures

. Proven experience developing

PowerShell

scripts for automation. Hands-on experience integrating with

AI/ML platforms

(e.g., Azure AI, Google Vertex AI). Demonstrable experience with

prompt engineering

for generative AI models. Solid understanding of

machine learning concepts

and data preparation techniques. Experience setting up and managing data integrations with

Azure

and/or

GCP

. Experience with

software testing

, data validation, and creating technical documentation.

Preferred Qualifications:

Familiarity with ML libraries and frameworks (e.g., scikit-learn, TensorFlow, PyTorch). Working knowledge of

Python

or

Java

. Experience with SQL Server

High-Availability (HA)

solutions (e.g., Always On). Experience with SQL Server Integration Services (SSIS) or Azure Data Factory. Microsoft, Azure, or Google Cloud certifications. * Bachelor's degree in Computer Science, Data Science, or equivalent experience.