Senior Software Engineer - Cloud Platform Engineering

About the Role

We are seeking a Senior Software Engineer to join a small, high-ownership team building robust cloud infrastructure for our globally deployed relational database engine. You will design and implement the application layers, business logic, and API workflows at the intersection of data management, cloud operations, and relational database services—critical components that enterprise applications depend on for correctness, performance, and governance. This is a hands-on, end-to-end role. You will lead features from whiteboard to production: owning implementation, writing clean and scalable code, and leveraging deep expertise in cloud orchestration to ensure robust deployment across multi-cloud environments. Proficiency in Terraform is essential for managing our complex infrastructure and ensuring reproducible deployments. Our lean is small by design, offering high individual impact and direct visibility into engineering strategy. The ideal candidate has scaled infrastructure across multiple cloud providers and approaches every challenge with an ownership mindset—shipping production-grade systems that set new industry standards.

Key Responsibilities

• 8+ years of experience in software development with deep expertise in distributed systems and cloud-native architecture.
• Proven track record of designing and operating multi-cloud infrastructure at scale across AWS, GCP, and Azure.
• Advanced proficiency in Terraform for Infrastructure as Code (IaC) and complex cloud orchestration.
• Expertise in containerization and orchestration using Kubernetes and Docker in production-grade environments.
• Experience building and maintaining robust CI/CD pipelines for automated, scalable deployments.
• Strong command of Go or Python for developing cloud-native applications, controllers, and automation tooling.
• BS/MS in Computer Science or a related technical field.
• Experience designing and implementing REST and/or gRPC APIs used by external consumers or frontend systems.
• Knowledge of MariaDB server is a plus.

Required Qualifications

Experience

• 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).

Technical Skills

• 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.