Product Specialist 3

2 weeks ago

Columbus, OH, United States EXOS Full time
Job Description

Position Summary

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).
Job Requirements

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.

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