AI Platform Developer

We are looking for a Senior Developer to join a small, high-ownership team building next-generation AI capabilities on top of a widely deployed relational database engine. You will design and implement the application layers, business logic, and API workflows that sit at the intersection of data management, AI applications, and relational database operations—components that enterprise AI applications depend on for correctness, performance, and governance. This is a hands-on, end-to-end role. You will go from whiteboard to production: owning the implementation of the features you build, writing clean and scalable application code, integrating AI orchestrators, and ensuring robust deployment across cloud and on-premises environments. Key Responsibilities: - End-to-End Feature Development: Lead the full software development lifecycle—from application design and API implementation to deployment and feature monitoring. - AI & Agent Integration: Connect production applications with agent frameworks (e.g., LangChain) and interoperability protocols (e.g., MCP, A2A) to support scalable, framework-agnostic APIs. - Database & Data Management: Develop secure, versioned application data models that enforce multi-tenant isolation, auditability, and data classification using advanced relational database features. - Multi-Cloud & Deployment: Build application services that deploy consistently across AWS, Azure, GCP, and on-premises environments, while utilizing automated CI/CD pipelines. - Application Performance: Define and meet feature-level performance goals through rigorous query optimization, code profiling, caching strategies, and proactive security practices. - Leadership & Collaboration: Maintain full ownership of application components, facilitate constructive design and code reviews, mentor team members, and drive decisions in an async-first environment. Required Qualifications: - 7+ years of professional software development experience, with at least 2 years focused on data-intensive applications, database-adjacent features, or enterprise software. - Demonstrated end-to-end ownership of a non-trivial production feature or module. - Hands-on production experience deploying, debugging, and managing application services across at least two major public clouds (AWS, Azure, GCP). - Experience building or integrating with vector databases, embedding pipelines, semantic search, or retrieval-augmented generation (RAG) systems. - Prior work building LLM-based applications or workflows using AI agent frameworks (LangChain, LangGraph, CrewAI, AutoGen, or equivalent). - Strong proficiency in Python for AI application development, alongside high proficiency in at least one backend language (such as Go, Java, or C++). - Deep, practical application of relational databases: writing complex SQL, structural indexing, query optimization, transactions, and schema design. - Experience implementing temporal data models, event-driven tracking, audit logs, or utilizing system-versioned tables. - Solid understanding of application security fundamentals: authentication, authorization, RBAC, row-level security, and multi-tenant data isolation at the application layer. - Proficiency with modern application monitoring tooling: structured logging, distributed tracing (OpenTelemetry), and functional alerting. - Experience designing and implementing REST and/or gRPC APIs used by external consumers or frontend systems. Preferred Qualifications: - Experience contributing to or maintaining open-source projects in the database, AI/ML application, or agent-tooling ecosystem. - Hands-on experience developing MCP servers or integrating A2A (Agent2Agent) protocols into production systems. - Familiarity with agent memory frameworks such as Mem0, Graphiti, or Letta. - Experience leveraging graph databases or multi-hop graph traversal (Neo4j, Kuzu, FalkorDB, or similar) within applications. - Background with in-memory data grids or semantic caching systems (Redis or similar) to optimize AI token usage. - Experience packaging applications for on-premises or air-gapped deployment environments, including regulated infrastructure. - Knowledge of MariaDB or MySQL application development, system-versioned tables, or temporal SQL.