Sr SQL/Oracle DBA
Job in
Alpharetta, Fulton County, Georgia, 30239, USA
Listed on 2026-08-15
Listing for:
Compunnel, Inc.
Full Time
position Listed on 2026-08-15
Job specializations:
-
Software Development
AI Engineer (Applied/Software), Data Engineering, Machine Learning/ ML Engineer
Job Description & How to Apply Below
If you are a passionate database engineer who would love to sit at the intersection of traditional enterprise database engineering and the emerging Gen AI revolution — building next-generation, AI-powered data solutions that transform how tens of thousands of users interact with the largest Human Capital Management system then we have a perfect role for you and we would like to have a discussion with you.
Education/ Experience / Certification
- Bachelor's degree in computer science or related field (required)
- Master's degree in computer science, Data Science, or AI/ML (preferred)
- 10+ years of experience as a Database Developer/DBA in a fast-paced agile environment
- 7+ years as an Oracle Developer/DBA with expert-level PL/SQL and SQL skills
- 2+ years of hands-on experience with Generative AI, LLMs, or ML pipelines in a production environment (preferred)
- Deep expertise in database internals, expert-level PL/SQL, SQL, and Python/Shell programming
- AWS Certified Machine Learning Specialty (plus)
- Design and build scalable database services and solutions to complex business problems
- Debug critical database issues and provide root-cause analysis with long-term solutions
- Research, Design, Develop, and/or modify applications using SQL, PL/SQL, Python, and AI-assisted development tools
- Prototype solutions and recommend adoption of new technologies including Generative AI and LLM-powered database tooling
- Development and Deployment of application database changes/releases across production and non-production environments
- Build and maintain LLM-powered database assistants using frameworks such as Lang Chain, Llama Index, or similar
- Develop Retrieval-Augmented Generation (RAG) solutions using structured/unstructured data from Oracle and PostgreSQL databases
- Integrate AI-powered query optimization tools to enhance database performance tuning workflows
- Leverage Git Hub Copilot, Amazon Q, or similar AI coding assistants to accelerate PL/SQL and Python development
- Build vector database integrations (pgvector, Oracle AI Vector Search) for semantic search capabilities
- Evaluate and adopt AI/ML model serving patterns (batch vs. real-time inference) for database-adjacent workloads
- Drive prompt engineering best practices for database-related AI applications
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