
Principal AI Engineer
- San Antonio, TX
- Permanent
- Full-time
Deadline to apply: Open until filledTasks and Responsibilities
- Lead the strategic vision and execution of enterprise-wide AI initiatives, ensuring alignment with organizational goals and digital transformation objectives.
- Collaborate with cross-functional teams to embed AI solutions into enterprise data workflows, ensuring models are well-governed, scalable, and deliver measurable business value by streamlining operations, improving decision-making, and unlocking actionable insights.
- Lead the design, development, and deployment of AI/ML solutions to support business functions such as forecasting, anomaly detection, computer vision, and natural language understanding.
- Lead the design, development and deployment of GenAI solutions using large language models (LLMs), image generation models, and retrieval-augmented generation (RAG) architectures for applications such as summarization, content generation, and intelligent automation.
- Analyze and communicate AI model results and accuracy in a way that is accessible to non-technical stakeholders, ensuring transparency and informed decision-making.
- Develop, lead, and continuously refine the organization's Generative AI (GenAI) strategy, identifying high-impact use cases and enabling enterprise-wide adoption.
- Partner with internal teams to embed GenAI into business processes, tools, and platforms to improve decision-making, customer engagement, and operational workflows.
- Establish and maintain MLOps frameworks to ensure reproducibility, scalability, and continuous improvement of deployed models.
- Guide model governance and ethical AI practices, including bias mitigation, explainability, version control, and compliance with regulatory, privacy, and security requirements.
- Embed AI risk management via risk assessments, audits, and ensuring alignment with enterprise standards in partnership with internal audit, legal, and regulatory teams.
- Stay abreast of advancements in AI/ML and GenAI research and technology; introduce and assess emerging tools and techniques for potential adoption.
- Create and maintain reusable AI components, services, and APIs to accelerate solution development and delivery.
- Drive AI literacy and GenAI understanding across the organization through training, enablement programs, and cross-functional collaboration.
- Engage with external vendors, research institutions, and AI partners to integrate best-in-class AI capabilities and platforms.
- Provide technical leadership, mentorship, and guidance to AI-focused staff and other cross-functional team members.
- Master’s degree in Computer Science, Data Science, Artificial Intelligence, or a related field, or equivalent work experience.
- Experience deploying large language models (LLMs), computer vision models, or generative AI technologies in enterprise settings.
- Hands-on knowledge of vector databases, embedding models, and prompt engineering for retrieval-augmented generation (RAG) systems.
- Certification in cloud AI/ML technologies (e.g., Azure AI Engineer, AWS Machine Learning Specialty, Google Professional ML Engineer).
- Prior experience working in the utility or energy sector and familiarity with AI applications in predictive maintenance, customer analytics, or load forecasting.
- Experience contributing to the development or execution of enterprise strategies involving advanced technologies such as AI, ML, or GenAI.
- Open-source contributions or published research in the field of AI/ML are a plus.