App Software & AI Engineer, Advisor

Join the Clean Energy Revolution

Become an App Software & AI Engineer, Advisor at Southern California Edison (SCE) and play a critical role in designing and delivering enterprise‑grade, intelligent software solutions that power essential utility operations and clean‑energy initiatives. In this role, you’ll serve as a technical advisor and hands‑on engineer, leading the delivery of complex full‑stack applications while integrating advanced AI capabilities to solve high‑impact business problems.

As an App Software & AI Engineer, Advisor, you’ll influence technical direction across multiple products and initiatives—helping teams translate ambiguous business needs into scalable architectures, guiding design decisions, and ensuring solutions align with enterprise standards and long‑term strategy. You’ll drive the adoption of AI across the software development lifecycle, mentor engineers at different stages of their careers, and partner closely with product, architecture, and business leaders to deliver secure, reliable, and future‑ready solutions that reduce carbon emissions and support a cleaner energy future.

• Build and deploy scalable enterprise applications using React, Angular, Node.js, Python, Express on Azure or GCP, mobile apps via iOS Swift and React Native, and low‑code/no‑code tools such as Power Platform.
• Design and implement AI‑integrated solutions using Azure OpenAI, Copilot Studio, and RAG architectures to build LLM‑powered agents, voice‑to‑text, image‑to‑text capabilities, and custom machine learning models.
• Provide technical guidance to the team, align with enterprise architecture, and drive consensus on technical decisions using software engineering principles, involving senior members and leadership in decision‑making.
• Mentor and coach junior and senior developers through code reviews, pair programming, and continuous learning initiatives, promoting best practices in Git Hub, CI/CD, and secure coding.
• Promote AI adoption across the organization by identifying opportunities, conducting POCs, and integrating AI into SDLC, product management, and operations workflows using tools such as Copilot and Power Platform AI.
• Collaborate with cross‑functional stakeholders—enterprise architecture, product owners, UX designers, and business leaders—to deliver well‑structured, maintainable, and impactful features for MVPs.
• Drive innovation by researching emerging technologies, proposing new tools and practices, and incubating ideas through rapid prototyping and MVP delivery using Design Thinking and Agile.
• Conduct technical evaluations, impact assessments, and solution prototyping to support agile delivery and continuous improvement of engineering processes.
• Ensure the protection of all physical, financial, and cybersecurity assets and properly handle private customer data, proprietary information, confidential medical records, and other highly sensitive information with the highest standards of conduct and integrity.

• Bachelor’s degree in Computer Science, Information Systems, or related field.
• Seven or more years of hands‑on full‑stack, enterprise‑scale experience in software development and delivery.
• One or more years of experience building, integrating, and scaling AI solutions.
• Three or more years of experience leading technical teams and mentoring and coaching other developers.

• Proven experience leading enterprise‑grade full‑stack application development, including designing scalable architectures and delivering maintainable solutions across multiple systems or domains.
• Deep hands‑on expertise with AI and Generative AI, including building and scaling solutions using large language models (LLMs) and designing Retrieval Augmented Generation (RAG) architectures to ground AI responses with enterprise data.
• Demonstrated ability to architect and deliver AI‑enabled applications and intelligent agents, translating complex business needs into secure, reliable, and production‑ready solutions.
• Three or more years of experience building cloud‑native solutions and deploying on cloud‑based architectures—Azure, GCP, and/or AWS—and understanding of…