Senior Software Engineer – Platform Graph

Jobtailor; United States; On-site; USD 140,000 - 190,000; Full time

Job summary

Jobtailor is seeking a senior backend engineer to design, build, and run a graph data platform and its microservices in C#/.NET. You will shape data models, schemas, and traversal patterns to answer security-related questions at scale.

You will validate designs against latency targets and contribute to a robust API layer (REST/GraphQL) consumed by multiple product teams, while leveraging AI coding tools and cloud-native deployments.

Qualifications

• Bachelor’s or Master’s degree in CS/SE or related field.
• 5+ years of production software experience in C#/.NET or comparable backend language.
• Practical experience using AI coding tools in production.
• Experience designing data models and schemas with query optimization.
• Experience with large-scale systems and graph traversals vs relational access patterns.
• Experience with relational and/or NoSQL databases (Azure SQL, Cosmos DB, PostgreSQL, MongoDB).
• Strong understanding of microservices and RESTful API design.
• Experience with cloud providers (Azure or others) and Kubernetes.

Responsibilities

• Help design, build, test, and run the graph data platform and its microservices in C#/.NET.
• Design graph data models, schemas, node/edge types, traversal patterns, and query patterns.
• Validate designs against scale and latency targets for systems with hundreds of millions to billions of entities.
• Build and evolve the API layer with REST and GraphQL contracts for other product teams.
• Collaborate on cloud-native deployments using Kubernetes and containers.

Skills

C#/.NET development

API design

Distributed systems

Graph data modeling

Cloud-native design

Education

Bachelor’s or Master’s in CS/SE

Tools

Claude Code

GitHub Copilot

Cursor

Kubernetes

Azure

Cosmos DB

PostgreSQL

MongoDB

Job description

• Help design, build, test, and run the graph data platform and its supporting microservices in C#/.NET, in line with Delinea’s cloud and security architecture standards.
• Build with AI every day. We’re an AI-first team: we lean on AI coding assistants and agents to design, write, and review code, and we expect everyone to keep getting sharper with them.
• Design the graph data models and schemas, including node and edge types, traversal patterns, and query patterns, to answer security questions such as relationship mapping, access-path analysis, and impact analysis.
• Validate designs against scale and latency targets for systems containing hundreds of millions to billions of entities.
• Build and evolve the API layer that other product teams query, keeping complexity behind clean, versioned REST and GraphQL contracts.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related field.
• 5+ years of experience writing production software in C#/.NET, or a comparable backend language, and building microservices.
• Practical experience using AI coding tools such as Claude Code, GitHub Copilot, Cursor, or similar tools in production work, along with the judgment to use them effectively.
• Experience designing data models and schemas, with a solid understanding of query optimization and distributed-data consistency trade-offs.
• Experience building systems that run at large scale and an understanding of how connected, relationship-shaped data and graph traversals differ from traditional relational access patterns.
• Experience with relational and/or NoSQL databases such as Azure SQL, Cosmos DB, PostgreSQL, or MongoDB.
• Strong understanding of microservices and RESTful API design.
• Experience with Microsoft Azure, or another major cloud provider, as well as cloud-native deployments using Kubernetes and containers.

Core Competencies

Demonstrates expertise in designing and building scalable graph data platforms and microservices using C#/.NET, with a strong focus on AI coding tools and cloud-native deployments. Proficient in data modeling, API design, and optimizing systems for performance and reliability.