Senior Software Engineer - Cloud Platform Engineering

• 5+ 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: you have taken something from functional specification through implementation to production.
• 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).

• 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.

Location & Job Info

Full-Time - Remote - US

• 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.