Principal Engineer

Req

NTT DATA strives to hire exceptional, innovative and passionate individuals who want to grow with us. If you want to be part of an inclusive, adaptable, and forward-thinking organization.

We are currently seeking a Principal Engineer to join our team in Charlotte, North Carolina (US-NC), United States (US).

The Principal Engineer provides technical leadership for the architecture, integration, governance, implementation, and operational support of enterprise AI engineering platforms. This role drives AI-enabled transformation across the Software Development Lifecycle (SDLC), including requirements management, design, development, testing, deployment, release management, and operations.

The position is responsible for designing and implementing scalable, secure, resilient, and compliant AI engineering solutions that integrate with enterprise development platforms, Dev Sec Ops  tool chains, cloud and on-premises infrastructure, observability solutions, and operational support processes.

The Principal Engineer partners with engineering, architecture, infrastructure, security, risk, compliance, and product teams to establish enterprise standards, reusable patterns, and best practices for AI-enabled software engineering capabilities.

• Serve as a technical advisor on complex AI engineering, platform, application, infrastructure, security, governance, and software delivery initiatives.
• Lead technical strategy and solution development for enterprise-scale engineering and platform challenges.
• Translate business requirements, technology strategy, risk considerations, and emerging AI capabilities into scalable engineering solutions.
• Provide technical leadership and guidance for enterprise AI enablement initiatives.
• Evaluate industry trends, tools, and technologies and recommend solutions that improve engineering productivity, delivery quality, operational effectiveness, and business outcomes.
• Influence architecture standards, engineering practices, integration patterns, and technology roadmaps across multiple teams.
• AI Engineering Platform Architecture
• Lead the architecture and evolution of enterprise AI engineering platforms across SaaS, cloud, desktop, and on-premises environments.
• Design scalable, resilient, secure, and supportable integration patterns for AI coding assistants, software engineering agents, and developer productivity platforms.
• Define enterprise architecture patterns for Model Context Protocol (MCP), MCP gateways, APIs, enterprise services, and platform interoperability.
• Provide hands‑on leadership for solution design, implementation, integration, testing, deployment, and operationalization.
• Establish reusable architecture patterns, engineering standards, reference architectures, implementation guidance, and platform controls.

• API architectures
• Authentication and authorization
• Network connectivity
• Service integration
• Platform security
• Scalability and resiliency
• AI-Enabled Software Development Lifecycle
• Lead integration of AI capabilities throughout the SDLC, including requirements, design, development, testing, deployment, release, and operations.
• Enable integration with requirements management and collaboration platforms.
• Support AI-enabled design workflows and architecture tooling.
• Integrate AI capabilities with developer platforms, source control systems, software supply chain tools, CI/CD platforms, and Dev Sec Ops  solutions.
• Enable integration with testing, validation, quality engineering, deployment, and release management platforms.
• Support integration with observability, monitoring, logging, and operational management platforms.
• Delivery, Security, Risk, and Governance
• Lead…