Principal Software Engineer

Prestige Staffing; New York (NY); Remote; USD 200.000 - 250.000; Vollzeit

Zusammenfassung

Prestige Staffing is seeking a Principal Software Engineer, AI-Native Engineering Lead, to guide a three-person pod building an AI operations product. This hands-on leadership role blends architecture, operations, and software delivery to shape an AI-enabled engineering culture.

The role is 100% remote in the United States, reporting to engineering leadership, with responsibility from design through deployment and the first 90 days of critical production work.

Qualifikationen

• Typically 8+ years of professional software engineering experience with technical leadership at Principal or Staff+ level.
• Strong software architecture and design skills balancing delivery speed, maintainability, reliability, security, and scalability.
• Experience delivering and operating production software end to end.
• Strong programming skills across a modern stack and ability to work across application layers.
• Deep understanding of testing strategies, CI/CD, version control, observability, security, and troubleshooting.
• Practical experience using AI coding agents in real engineering workflows.
• Ability to translate ambiguous business problems into 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 and leading small autonomous teams.
• Experience with agentic coding workflows and AI-enabled development infrastructure preferred.

Aufgaben

• Lead the technical direction, architecture, design, and implementation strategy for applications, services, and systems.
• Work hands-on alongside two engineers and AI coding tools.
• Translate product goals into pragmatic, maintainable technical solutions.
• Establish lightweight engineering standards, conventions, and documentation.
• Integrate AI coding agents into requirements analysis, code generation, testing, and documentation.
• Break complex initiatives into small, independently testable increments.
• Evaluate AI-generated code and decide on acceptance or changes.
• Own production delivery from problem definition through deployment and monitoring.
• Establish observability, deployment automation, rollback procedures, and safeguards.
• Define quality controls including automated testing, code review, and security checks.
• Develop guardrails for AI access to source code and production data.
• Mentor engineers through pairing, reviews, and design discussions.
• Foster ownership, accountability, and continuous learning; share AI practices broadly.
• Deliver meaningful production capabilities within 90 days and establish a repeatable AI-native model.
• $200,000–$250,000 annual compensation; authority to shape processes for a three-person team.
• Own a focused area within a new AI operations product; establish a repeatable AI development model.

Kenntnisse

Technical leadership

Software architecture

CI/CD

AI tooling

Mentoring

Cross-functional

Code reviews

Observability

Problem solving

Communication

Tools

Claude Code

OpenAI Codex

Jobbeschreibung

Principal Software Engineer, AI-Native Engineering Lead

Pay

$200,000–$250,000 annually

Location

100% Remote

Summary

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.

Requirements

• 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

Responsibilities

• 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, 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
• $200,000–$250,000 annual compensation
• Opportunity to establish the processes and technical direction for a three-person engineering team
• Ownership of a focused area within a new AI operations product
• Opportunity to shape a repeatable model for AI-augmented software engineering