6 days ago
Responsibilities
- Analyze SQL Server stored procedures to identify business logic, dependencies, and data access patterns.
- Refactor stored procedures, execute database migrations, optimize queries and indexes, and maintain data integrity, availability, and backward compatibility.
- Implement CDC, transactional outbox, event publishing, database-change testing, and validation processes.
- Build embedding, vector storage, synchronization, semantic search, hybrid retrieval, and RAG evaluation pipelines.
- Develop retrieval APIs and services consumed by AI applications and agents.
- Design ETL/ELT, API-based ingestion, event-streaming, and batch-processing workflows across relational, cloud, and NoSQL data platforms.
- Implement data quality, validation, observability, monitoring, and infrastructure-as-code for database provisioning and configuration.
- Use AI coding assistants and develop prompts, scripts, workflows, and internal tools for database analysis, documentation, migration, and engineering automation.
- Partner with application, platform, and AI/ML engineers; participate in reviews; troubleshoot production issues; document solutions; and mentor engineers.
Requirements
- Strong hands-on experience with SQL Server, T-SQL, stored procedures, query optimization, and execution plans.
- Experience modernizing legacy database systems and decomposing complex database logic into application or service architectures.
- Strong understanding of relational database design, indexing, transactions, data integrity, and performance engineering.
- Experience building production-grade data pipelines and integrating data through APIs, events, and batch processes.
- Experience with one or more of PostgreSQL, Snowflake, MongoDB, or Cosmos DB.
- Practical experience with vector databases, embeddings, semantic search, RAG, or AI data pipelines.
- Understanding of event-driven architecture patterns such as CDC and transactional outbox.
- Experience with cloud platforms and infrastructure-as-code, preferably AWS or Azure and Terraform.
- Strong software engineering fundamentals, including version control, automated testing, CI/CD, and code review practices.
- Ability to use AI coding assistants effectively and incorporate AI into daily engineering work.
- Preferred qualifications include LLM or agentic application data infrastructure, Pinecone, Azure AI Search, OpenSearch, pgvector, Kafka, retrieval services, RAG evaluation frameworks, AI-powered developer tools, and large-scale distributed cloud-native environments.
Benefits
- Health, dental, and vision insurance.
- Retirement savings plan, paid time off, health savings account, flexible spending accounts, life insurance, and disability insurance.
- Tuition reimbursement and additional comprehensive benefits.
- Non-sales roles are typically eligible for a quarterly or annual bonus under the applicable plan.
Tech Stack
Categories
AI ApplicationsData Engineering
About WEX
WEX (NYSE: WEX) is the global commerce platform that simplifies the business of running a business. WEX has created a powerful ecosystem that offers seamlessly embedded, personalized solutions for its customers around the world. Through its rich data and specialized expertise in simplifying benefits, reimagining mobility and paying and getting paid, WEX aims to make it easy for companies to overcome complexity and reach their full potential. For more information, please visit www.wexinc.com.