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# Principal Software Engineer

- **Company:** PRESTIGE STAFFING INC
- **Location:** New York, NY, United States (Remote available)
- **Experience:** Expert
- **Salary:** $200,000.0 - $250,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Application Layers, Architectural Patterns, Automation of Tests, Static Program Analysis, Code Generation, Code Review, Computer Programming, Continuous Integration, Customer Data Management, Software Debugging, Software Architecture, Software Engineering, Strategies of Testing, Claude Code, Software Security, AI Coding Agents, Integration Tests, Deployment Automation, OpenAI Codex, Code Restructuring, Software Version Control, Service Stack
- **Published:** November 6, 2026
- **Apply:** https://www.juju.com/job/2_169508854

## About the Role

* Typically 8+ years of professional software engineering experience, with technical leadership at the Principal or Staff+ level
 * Strong software architecture and design skills, including the ability to balance delivery speed, maintainability, reliability, security, and scalability
 * Demonstrated experience delivering and operating production software end to end
 * Strong programming skills in at least one modern technology stack, with the ability to work across application layers as needed
 * Deep understanding of testing strategies, CI/CD, version control, observability, application security, and production troubleshooting
 * Practical experience using AI coding agents, such as Claude Code, OpenAI Codex, or comparable tools, in real engineering workflows
 * Ability to turn ambiguous business problems into clearly defined technical tasks and drive them through completion
 * Excellent technical communication, problem-solving, mentoring, and decision-making skills
 * Track record of owning business and technical outcomes-not just assigned implementation tasks
 * Experience leading small, autonomous, cross-functional engineering teams preferred
 * Experience with agentic coding workflows, parallel AI task execution, repository-level instructions, or automated validation pipelines preferred
 * Experience creating developer platforms, reusable engineering templates, or AI-enabled development infrastructure preferred

## Description

Lead a highly autonomous three-person engineering pod focused on building an AI operations product. This hands-on Principal Engineer role combines technical leadership, architecture, software development, and AI-assisted engineering to deliver reliable production capabilities with speed and discipline. You'll have the opportunity to shape how an AI-native engineering team operates from the ground up., * Lead the technical direction, architecture, design, and implementation strategy for applications, services, and systems

 * Work hands-on alongside two supporting engineers and AI coding tools
 * Translate product and business objectives into pragmatic, maintainable technical solutions
 * Establish lightweight engineering standards, coding conventions, architectural patterns, and documentation practices
 * Integrate AI coding agents into requirements analysis, code generation, testing, debugging, refactoring, code review, and documentation
 * Break complex initiatives into small, well-defined, independently testable increments
 * Evaluate AI-generated code critically and determine when to accept, modify, or reject proposed changes
 * Own production delivery from problem definition through deployment, monitoring, operational support, and continuous improvement
 * Establish observability, deployment automation, rollback procedures, and operational safeguards
 * Define practical quality controls, including automated testing, code review, xrbllit integration testing, static analysis, security checks, and production validation
 * Develop guardrails for AI access to source code, credentials, production systems, customer data, and other sensitive resources
 * Mentor and enable supporting engineers through pairing, code reviews, design discussions, and progressively challenging assignments
 * Build a culture of ownership, experimentation, direct communication, accountability, and continuous learning
 * Share effective AI-assisted engineering practices with the broader engineering organization
 * Deliver meaningful production capabilities within the first 90 days while establishing a repeatable AI-native development model