Principal IT Architect

Requisition ID: 96740

NextEra Energy Resources is one of America’s largest wholesale electricity generators, harnessing diverse energy sources to power progress. We deliver tailored energy solutions that fuel economic growth, strengthen communities, and help customers achieve their energy goals. Ready to make a lasting impact? Take the next step in your career with us!

Position Specific Description

The Principal IT Architect will serve as the senior technical leader for applications and platforms supporting NEET Transmission and NEER Development. This role will partner with Enterprise Architecture, Cybersecurity, Data Governance, Cloud Infrastructure, business stakeholders, and delivery teams to define and execute technology modernization strategies.

The successful candidate will translate enterprise technology direction into practical roadmaps, reference architectures, engineering standards, and scalable solutions. This individual will lead through technical expertise and influence, guide the organization toward an AI-first future, and establish the architecture, engineering practices, and governance needed to deliver secure, reliable, and production-ready AI-enabled solutions.

Key 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 ensure portfolio solutions align with enterprise strategies, standards, and approved technology patterns.

• Provide architecture leadership for complex 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 appropriate rehost, replatform, refactor, replace, rebuild, or retire strategies.

• Provide expert guidance for AWS and/or Google Cloud Platform infrastructure architectures, including compute, storage, networking, identity, security, observability, resiliency, disaster recovery, and cost optimization.

• Lead the 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 formal 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 addressing security, privacy, data governance, explainability, auditability, model risk, human accountability, and regulatory requirements.

• Advance MLOps and LLMOps practices for model and prompt versioning, deployment, evaluation, monitoring, observability, governance, incident management, and performance optimization.

• Guide development teams in the use of AI-assisted engineering, agentic development workflows, and AIDLC practices while establishing appropriate 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 clearly to technical teams, business partners, and senior leadership.

• Mentor developers, engineers, architects, and technical leads while providing direction to vendors, consultants, and delivery partners.

• Build AI architecture and engineering capability across the team through reusable patterns, technical standards, coaching, demonstrations, and communities of practice.

Required Qualifications

• 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+ 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 (IaaS).

• 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.

• Demonstrated 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, including 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.

Preferred Qualifications

• Experience in the utility, energy, critical-infrastructure, or another regulated industry.

• Experience supporting transmission planning, interconnection, renewable-energy development, engineering, modeling, or analytical platforms.

• Demonstrated 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 a comparable architecture or AI certification.

• Experience with enterprise architecture frameworks and architecture-governance practices.

• Experience leading distributed internal, vendor, and consulting teams.

NextEra Energy offers a wide range of benefits to support our employees and their eligible family members. Click here to learn more.

Employee Group: Exempt
Employee Type: Full Time
Job Category: Information Technology
Organization: NextEra Energy Resources, LLC
Relocation Provided: Yes, if applicable

NextEra Energy is an Equal Opportunity Employer. Qualified applicants are considered for employment without regard to race, color, age, national origin, religion, marital status, sex, sexual orientation, gender identity, gender expression, genetics, disability, protected veteran status or any other basis prohibited by law.

NextEra Energy and provides reasonable accommodation in its application and selection process for qualified individuals, including accommodations related to compliance with conditional job offer requirements, consistent with federal, state, and local laws. Supporting medical or religious documentation will be required where applicable and permitted by applicable law. To request a reasonable accommodation, please send an e-mail to recruiting-coordinator.sharedmailbox@nexteraenergy.com, providing your name, telephone number and the best time for us to reach you.

NextEra Energy will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or (c) consistent with the contractor’s legal duty to furnish information.

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