Principal Engineer Jobs in Charlotte, NC

Role: Principal Engineer

Location of work: Charlotte, NC or Irving, TX (Onsite)
Duration: 12 months Contract

Description

The Principal Engineer will provide hands-on technical leadership for the architecture, integration, governance, and operationalization of enterprise AI engineering platforms. The role will drive AI-enabled transformation across the end-to-end Software Development Lifecycle (SLC), including requirements, design, development, testing, deployment, release, and operations. The ideal candidate will be a seasoned engineering and platform architect with experience integrating AI coding assistants, autonomous software engineering agents, Model Context Protocol (MCP) services, SaaS and on-premises platforms, developer toolchains, DevSecOps automation, security controls, and production operations. The role will lead the evolution of enterprise AI enablement patterns supporting platforms such as Devin and other AI-assisted engineering solutions. The Principal Engineer will guide integration with requirements management, source control, CI/CD, security scanning, testing, release management, observability, and IT service management platforms while ensuring alignment with enterprise security, technology risk, compliance, and operational requirements.

In this role, you will:

- Act as a trusted technical advisor to senior leadership on highly complex AI engineering, platform, application, infrastructure, security, governance, and software delivery decisions.
- Lead the strategy and resolution of enterprise challenges that require evaluation across multiple technology areas and organizations.
- Translate product objectives, enterprise technology strategy, risk requirements, and emerging AI capabilities into scalable engineering solutions.
- Provide vision, direction, and hands-on technical expertise for innovative, long-term, and enterprise-scale AI enablement capabilities.
- Maintain knowledge of industry practices and emerging technologies, recommending innovations that improve engineering productivity, delivery quality, operational effectiveness, or business outcomes.
- Strategically engage with professionals and leaders across DT and influence architecture standards, engineering practices, integration patterns, and modernization roadmaps.

Key Responsibilities

AI Enablement Architecture and Engineering Leadership

- Lead the architecture and continued evolution of enterprise AI engineering capabilities across SaaS, cloud, desktop, and on-premises environments.
- Design scalable, resilient, secure, and compliant integration patterns for AI coding assistants and software engineering agents.
- Define enterprise patterns for Model Context Protocol (MCP), remote and hosted MCP services, MCP gateways, enterprise tools, APIs, and platform interoperability.
- Provide hands-on technical leadership for solution design, implementation, integration, and operationalization.
- Establish reusable architecture patterns, engineering standards, reference implementations, implementation playbooks, and platform guardrails.
- Lead high-level architecture, end-to-end flow, authentication and authorization, network connectivity, API contract, and service integration design.

AI-Enabled Software Development Lifecycle

- Drive AI integration across the Define, Design, Develop, Test, Deploy, Release, and Operate phases of the SDLC.
- Enable integrations with requirements and collaboration platforms, including Jira and Confluence.
- Enable design workflows and integrations with tools such as Figma and enterprise architecture services.
- Integrate AI capabilities with developer and software supply chain platforms, including GitHub, GitHub Actions, Artifactory, Sonar, Checkmarx, and Black Duck.
- Enable testing and validation integrations with platforms such as JMeter, HyperExecute, Report Portal, BrowserStack, and BlazeMeter.
- Integrate deployment and release workflows with platforms such as Harness, Ansible, and ServiceNow.
- Enable operational integrations with observability and monitoring platforms such as Splunk and AppDynamics.

Delivery, Validation, Security, and Governance

- Lead delivery from initiation and requirements through architecture and design, build and configuration, validation, security and governance, production readiness, and go-live.
- Define functional and non-functional requirements and perform tool capability assessments.
- Guide service account and secret configuration, router or gateway integration, proxy developer and connectivity with target services and tools.
- Lead non-production deployment and connectivity, functional, integration, security, user acceptance and performance testing.
- Initiate and support architecture, cyber security, third-party or SaaS, risk, compliance, and governance reviews and approvals.
- Ensure solutions comply with enterprise security, data protection, technology risk, regulatory, operational requirements.

Production Readiness and Operations

- Drive change request initiation, production readiness review, and required change approvals.
- Establish monitoring, logging, alerting, incident response, support, and service management standards.
- Develop runbooks, playbooks, game plans, rollback strategies, and operational handoff models.
- Guide production deployment, post-implementation testing, monitoring and alerting review, and continuous operational improvement.
- Partner with DevOps, Release Engineering, and Site Reliability Engineering teams to improve platform reliability, resilience, and supportability.

Cross-Functional Collaboration

- Partner with product owners, UX designers, developers, application architects, testers, DevOps engineers, release technology leads, release engineers, and site reliability engineers.
- Collaborate with Architecture, Cybersecurity, Infrastructure, Platform Engineering, Application Development, Quality Engineering, Risk, Compliance, and Operations teams.
- Facilitate architecture discussions and build alignment across product, engineering, governance, infrastructure, and operational stakeholders.
- Clearly communicate complex technical concepts, architecture decisions, risks, trade-offs, and recommendations to technical and executive audiences.
- Mentor senior engineers and architects and help build enterprise communities of practice for AI-enabled engineering.

Required Qualifications:

- 7+ years of Engineering experience, or equivalent demonstrated through one or a combination of work experience, training, military experience, or education.
- 5+ years of technical leadership experience driving enterprise-scale engineering initiatives, architecture programs, platform integrations, or technology transformations.
- 5+ years of hands-on software engineering, platform engineering, DevOps, API integration, cloud engineering, or infrastructure automation experience.
- Experience designing and implementing enterprise-grade solutions across modern SLC, DevSecOps, CI/CD, cloud, SaaS, and on-premises environments.
- Experience with enterprise architecture, APIs, service integration, authentication, authorization, secrets management, network connectivity, and security controls.
- Experience leading complex cross-functional technology initiatives and influencing engineering, product, architecture, security, risk, and operations stakeholders.
- Experience establishing production readiness, observability, operational support, governance, and continuous improvement practices.

Desired Qualifications:

- Experience with Generative AI, Agentic AI, AI engineering platforms, Large Language Models, and AI-assisted software engineering.
- Knowledge of Model Context Protocol (MCP), MCP gateways, agent orchestration, tool integration, and secure enterprise AI architecture patterns.
- Experience integrating AI-powered developer productivity tools, coding assistants, or autonomous software engineering agents into enterprise workflows.
- Experience with GitHub Enterprise, GitHub Actions, Jira, Confluence, Figma, Artifactory, Sonar, Checkmarx, Black Duck, BrowserStack, BlazeMeter, Report Portal, Harness, ServiceNow, Splunk, AppDynamics, Ansible, or comparable platforms.
- Experience delivering enterprise technology solutions in a regulated financial services environment.
- Strong understanding of secure architecture, SaaS risk assessment, third-party governance, data protection, technology risk, compliance, and operational controls.
- Demonstrated ability to create reusable frameworks, reference implementations, engineering standards, technical guidance, adoption roadmaps, and enablement programs.
- Ability to influence technical strategy and architecture decisions across multiple organizations and senior leadership teams.
- Excellent communication, stakeholder management, and executive presentation skills.