Senior Software Engineer

Description

Quantum Sky is searching for a Senior Full-Stack Software Engineer to build and enhance cloud-based and on-premise cybersecurity and compliance applications for highly regulated environments. This is a hands-on development role

The ideal candidate is a strong software engineer with experience developing applications in FISMA/FedRAMP environments and familiarity with NIST security and compliance frameworks. They are comfortable owning software across the full development lifecycle—from design and development through CI/CD, deployment, and production operations—and can effectively work across software development, cloud infrastructure, cybersecurity, and compliance.

This role includes work on data-intensive risk and compliance analytics products: applications that ingest security and inventory data from multiple, heterogeneous, and sometimes inconsistent sources, normalize it into a consistent internal model, and present risk, gap, and prioritization analytics to different classes of users (executive, program-management, and technical).
Responsibilities:

- Design, develop, test, and maintain full-stack application capabilities with an emphasis on secure, scalable, maintainable, and production-ready software.

- Develop backend services, APIs, integrations, automation, and supporting tools.

- Build new product capabilities and enhance existing functionality across cloud-based/on-premise cybersecurity and compliance applications, including backend services and user-facing application features.

- Design and implement integrations with cloud services, security technologies, vulnerability management platforms, monitoring solutions, and third-party systems using REST APIs and structured.

- Develop capabilities that ingest, process, correlate, and present security and compliance information while automating workflows such as security monitoring, vulnerability management, evidence collection, control management, and reporting.

- Design data models and normalization/correlation logic capable of reconciling overlapping or conflicting records from multiple independent data sources into a single, consistent, and traceable representation, preserving source provenance and confidence.

- Design and implement configurable scoring, prioritization, or risk-analytics logic as discrete, testable components rather than embedded business rules — supporting features such as gap analysis, trend analysis, and what-if/scenario comparison.

- Model relationships and dependencies between assets, systems, and organizational entities in a way that supports drill-down analysis and can scale toward graph-based or dependency-graph representations as products mature.

- Implement role-based access control and role-differentiated views so that different user types (executive, program/system management, technical) see appropriately scoped and appropriately detailed information.

- Develop, maintain, and improve CI/CD pipelines and automated deployment processes that support application builds, automated testing, security validation, and reliable deployment across development, staging, and production environments.

- Build, deploy, and support containerized and cloud-native applications, collaborating with cloud and DevOps engineers to improve application scalability, reliability, observability, security, and performance.

- Use AI-assisted software development tools such as Claude Code, OpenAI Codex, Cursor, GitHub Copilot, or similar technologies as part of day-to-day engineering workflows to accelerate coding, debugging, refactoring, testing, documentation, and code analysis.

- Apply engineering judgment when working with AI-generated code and recommendations, validating outputs for correctness, security, maintainability, performance, and alignment with engineering standards.

- Troubleshoot complex application, integration, deployment, and production issues, identify root causes, and implement sustainable solutions.

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