Senior Database Developer – AI​/ML Data Systems

Santa Ana, CA

Work Location:

At Profit Recovery Partners (PRP), we believe that collaboration and innovation thrive when we're together. This position is
fully onsite
at our Santa Ana office, allowing for real-time teamwork, immediate problem-solving, and a strong sense of community among our team members.

As a Senior Database Developer – AI/ML Data Systems, you will be a senior member of our database development team, responsible for leading the design, development, optimization, and maintenance of complex database systems that power both traditional business applications and modern AI-driven solutions. You will provide technical expertise and guidance to the team, drive innovation in AI-enabled data engineering, and contribute to the overall data and AI strategy of the organization.

In this role, you will collaborate with stakeholders, architects, data scientists, and engineering teams to deliver scalable, efficient, and secure database and AI data infrastructure. This position requires strong leadership skills, expert-level knowledge of database management systems, hands‑on experience with AI/ML data technologies, and the ability to solve complex data challenges.

• Lead the design, development, and implementation of complex and highly scalable database systems, including data models, schemas, tables, views, and stored procedures, supporting both transactional workloads and AI/ML applications.
• Architect and implement data infrastructure for AI solutions, including vector databases, embedding stores, and semantic search capabilities (e.g., Azure AI Search, pgvector, Pinecone) to support retrieval‑augmented generation (RAG) and other LLM‑powered applications.
• Design and build data pipelines that prepare, transform, and serve high‑quality data for machine learning models, LLM fine‑tuning, and analytics, including feature engineering and feature store management.
• Integrate AI services and APIs (e.g., Azure OpenAI, Anthropic, OpenAI) into database‑driven applications and workflows, including intelligent document processing, natural language querying, and automated data classification.
• Leverage AI‑assisted development tools (e.g., Git Hub Copilot, AI code assistants) to accelerate development, improve code quality, and champion responsible adoption of these tools across the team.
• Collaborate with cross‑functional teams, including software developers, data scientists, system administrators, and business analysts, to understand requirements, provide technical expertise, and deliver data and AI solutions that meet business objectives.
• Provide technical support and training to users and clients on the use of data systems, AI‑enabled tools, processes, and custom applications built.
• Conduct advanced performance tuning and optimization activities, including query optimization, indexing strategies (including vector indexing), and database configuration enhancements, to maximize system performance and efficiency. Develop and implement proactive monitoring solutions to detect and resolve performance issues, system bottlenecks, and database errors in a timely manner.
• Investigate and resolve complex database‑related issues, including data anomalies, performance bottlenecks, and system failures, using advanced troubleshooting techniques and tools.
• Contribute to data and AI architecture standards, guidelines, and governance frameworks, ensuring data consistency, integrity, interoperability, and responsible AI practices across the organization.
• Develop and implement robust security measures, access controls, and data encryption techniques to protect sensitive data including data used in AI systems and ensure compliance with industry regulations, data privacy requirements, and best practices.
• Provide technical leadership, mentorship, and guidance to junior members of the database development team, fostering a collaborative and knowledge‑sharing environment.
• Stay abreast of emerging database and AI technologies, trends, and industry best practices; evaluate their applicability to the organization’s data landscape and propose innovative solutions.
• Develop and implement data quality assurance processes,…