Principal IT Architect

NextEra Energy•Juno Beach, FL

About The Position

The Principal IT Architect serves as the senior technical leader for applications and platforms supporting NEET Transmission and NEER Development. The role partners with Enterprise Architecture, Cybersecurity, Data Governance, Cloud Infrastructure, business stakeholders, and delivery teams to define and execute technology modernization strategies. The architect translates enterprise technology direction into practical roadmaps, reference architectures, engineering standards, and scalable solutions. Through technical expertise and influence, the role guides the organization toward an AI-first future and establishes the architecture, engineering practices, and governance needed to deliver secure, reliable, production-ready AI-enabled solutions. The position develops and maintains high-level logical and technical IT architecture, provides strategic decision-making and technical guidance, and facilitates delivery of business outcomes through technology decisions. It leads architecture and modernization initiatives, establishes technology standards and governance, evaluates emerging technologies, and mentors technical specialists.

Requirements

Bachelor's or master's degree in Computer Science, Information Technology, Engineering, Information Systems, Data Science, or a related discipline, or equivalent relevant professional experience.
10 or more years of progressive experience in information technology, software engineering, solution architecture, enterprise architecture, cloud architecture, application development, or related disciplines.
Demonstrated experience leading architecture for complex enterprise applications, platforms, or modernization programs.
Expert-level knowledge of AWS and/or Google Cloud Platform Infrastructure as a Service.
Experience designing secure, resilient, scalable, and cost-effective cloud or hybrid-cloud architectures.
Strong knowledge of application architecture, integration patterns, APIs, data architecture, cybersecurity, and modern software-engineering practices.
Experience developing architecture roadmaps and translating target-state designs into executable delivery plans.
Hands-on experience designing and delivering production-grade machine learning and generative AI solutions in an enterprise environment.
Deep understanding of transformer models, large language models, retrieval-augmented generation, agent frameworks, multi-agent architectures, and model orchestration.
Hands-on experience with one or more enterprise AI platforms, such as Amazon Bedrock, Amazon SageMaker, Google Vertex AI, Gemini, Azure OpenAI, or comparable services.
Experience with vector databases, embeddings, semantic search, orchestration layers, enterprise data grounding, and AI observability.
Experience architecting production agent systems using tool integration, function calling, context engineering, enterprise APIs, and controlled access to business systems.
Experience applying MLOps and LLMOps practices, including model, prompt, and configuration versioning; automated evaluation; deployment; monitoring; governance; and lifecycle management.
Experience establishing formal evaluation and validation processes for AI solutions, including prompt evaluation, hallucination mitigation, safety guardrails, quality thresholds, and human validation.
Strong understanding of Responsible AI, AI security, data privacy, model and vendor risk, explainability, auditability, least-privilege access, and human accountability.
Experience integrating AI solutions with enterprise applications, data platforms, APIs, identity services, and cloud infrastructure.
Experience partnering with Enterprise Architecture, Cybersecurity, Data Governance, Cloud Infrastructure, and other specialized technology teams.
Ability to lead technical teams and influence decisions without direct reporting authority.
Strong business-facing communication, facilitation, and executive-presentation skills.
High school diploma or GED.
At least 6 years of experience, as listed in the general required qualifications.

Nice To Haves

Experience in the utility, energy, critical-infrastructure, or another regulated industry.
Experience supporting transmission planning, interconnection, renewable-energy development, engineering, modeling, or analytical platforms.
Ability to incorporate total cost of ownership into architecture recommendations, including cloud consumption, model inference and training costs, software licensing, vendor costs, implementation effort, ongoing support, operational complexity, and modernization benefits.
Experience applying FinOps practices, cloud-cost governance, usage forecasting, and cost-performance optimization when evaluating architecture changes.
Experience comparing the cost, value, risk, and long-term maintainability of custom-built, vendor-provided, open-source, and managed AI services.
Experience with AI model gateways, Model Context Protocol, agent-to-agent communication, AI evaluation platforms, or enterprise AI observability tools.
Experience developing AI reference architectures, reusable components, enterprise standards, or AI governance controls.
AWS Certified Solutions Architect - Professional, Google Cloud Professional Cloud Architect, AWS Certified Machine Learning Engineer, Google Cloud Professional Machine Learning Engineer, or comparable architecture or AI certification.
Experience with enterprise architecture frameworks and architecture-governance practices.
Experience leading distributed internal, vendor, and consulting teams.
Bachelor's degree.

Responsibilities

Define current-state, target-state, and transition architectures for the NEET Transmission and NEER Development technology portfolios.
Develop and execute modernization roadmaps that improve scalability, reliability, cybersecurity, supportability, and cost efficiency.
Serve as the primary liaison with Enterprise Architecture and align portfolio solutions with enterprise strategies, standards, and approved technology patterns.
Provide architecture leadership for initiatives involving transmission planning, interconnection, renewable development, engineering analysis, modeling, analytics, and related business processes.
Lead solution design across application, integration, API, data, cloud, infrastructure, security, machine learning, and generative AI domains.
Establish reusable reference architectures, design patterns, architecture decision records, and technical standards.
Evaluate legacy applications and recommend rehosting, replatforming, refactoring, replacement, rebuilding, or retirement strategies.
Provide guidance on AWS and/or Google Cloud Platform infrastructure architecture, including compute, storage, networking, identity, security, observability, resiliency, disaster recovery, and cost optimization.
Lead end-to-end architecture and delivery of machine learning and generative AI solutions from use-case evaluation and prototyping through production deployment, monitoring, support, and lifecycle management.
Define scalable patterns for retrieval-augmented generation, vector search, embeddings, multi-agent architectures, model orchestration, tool use, function calling, and enterprise-system integration.
Establish AI evaluation and validation practices, including prompt evaluation, model-quality testing, grounding and citation validation, safety guardrails, hallucination mitigation, human-in-the-loop controls, and measurable acceptance criteria.
Establish Responsible AI architecture practices for security, privacy, data governance, explainability, auditability, model risk, human accountability, and regulatory requirements.
Advance MLOps and LLMOps practices for versioning, deployment, evaluation, monitoring, observability, governance, incident management, and performance optimization.
Guide development teams in AI-assisted engineering, agentic development workflows, and AIDLC practices, with quality gates for AI-generated code, tests, designs, and documentation.
Lead architecture reviews, technical evaluations, proofs of concept, vendor assessments, and build-versus-buy decisions.
Communicate architecture options, risks, costs, trade-offs, and recommendations to technical teams, business partners, and senior leadership.
Mentor developers, engineers, architects, and technical leads, and provide direction to vendors, consultants, and delivery partners.
Build AI architecture and engineering capability through reusable patterns, technical standards, coaching, demonstrations, and communities of practice.
Work with business partners to analyze strategy and trends and define requirements, principles, and models that guide technology decisions.
Communicate and enforce technology standards with business partners.
Understand industry trends and the practical application of existing, new, and emerging technologies.
Drive digital innovation and develop roadmaps using technologies and approaches that fulfill strategic business plans.
Define high-level migration plans to address gaps in the current state.
Coach, mentor, and lead technical subject-matter experts to enable consistency across technology architectures.
Design and own governance, assurance, and standards activities for enterprise technology architecture compliance.
Oversee and facilitate evaluation, risk assessment, selection, and design of hardware and software technology and product standards.
Deliver technology architecture artifacts, including reference architectures or concepts of operation.
Perform other job-related duties as assigned.