AI Engineer at RNGD in Metairie, LA

About the Company

RNGD is a rapidly scaling organization emerging as a nationally recognized leader in construction through our unique Renegade mindset focused on innovation, creativity, and culture. The team is made up of a highly engaged group of seasoned professionals and emerging leaders. We are creators who believe that what we build drives the growth of our cities and that to fulfill our mission, we must constantly challenge the old way of doing things. Headquartered in New Orleans, Louisiana, we thrive on building communities, building teams, building leaders, and growing the business throughout the Southeast region with additional offices in Mississippi, Tennessee, and Alabama.

About the Role 

We’re looking for an AI Engineer that will serve as a foundational contributor responsible for applying machine learning, generative AI, workflow automation, and modern data engineering to real-world construction and business challenges. This role focuses on building, evaluating, iterating, and deploying AI models, retrieval-augmented generation (RAG) applications, agentic systems, and intelligent workflows under the direction of senior leadership. The AI Engineer contributes hands-on development, low-code automation, model experimentation, and deployment support to create AI-enabled tools that improve decision-making, reduce manual effort, and generate measurable business value.

Core Responsibilities

• Low-Code Automation & Workflow Development

• • Develop and maintain low-code automations and internal tools using platforms such as Power Automate, Power Apps, and related systems.
  • Build lightweight integrations between systems including Procore, Spectrum, SharePoint, and other internal platforms to streamline workflows and data movement.
  • Prototype and deploy automations that reduce manual work, improve visibility, and increase operational consistency.
  • Assist in integrating AI-enabled functionality into low-code solutions and internal AI tools.

• AI Development & Model Experimentation

• • Assist in building, fine-tuning, and evaluating machine learning and generative AI models for prioritized business use cases.
  • Prototype applications using large language models (LLMs), embeddings, vector databases, graph structures, and retrieval-augmented generation (RAG) workflows.
  • Develop scripts and workflows for data preparation, model inference, evaluation, and experimentation.
  • Build AI agents and intelligent systems that incorporate internal organizational terminology, operational knowledge, and business context.
  • Support prompt engineering, prompt evaluation, and iterative refinement of AI-enabled applications.

• Solution Deployment & Integration

• • Package and deploy AI models and services into internal tools and cloud environments.
  • Integrate AI capabilities with operational systems and business platforms under guidance from senior leadership.
  • Support testing, monitoring, iteration, and optimization of deployed AI solutions.
  • Assist in transitioning prototypes into scalable, documented production workflows.

• Data Engineering & Pipeline Support

• • Build and maintain lightweight data pipelines for ingestion, cleaning, transformation, and model consumption.
  • Work with structured and unstructured datasets including documents, images, logs, and operational records.
  • Support development of training, validation, and evaluation datasets.
  • Collaborate with analytics and technology teams to improve data quality, access, and governance practices. 

• Cross-Functional Collaboration

• • Partner with operations, innovation, IT, and external consultants to identify workflow opportunities and AI use cases.
  • Participate in working sessions, requirements gathering, prototype demonstrations, and solution reviews.
  • Document lessons learned and contribute to prioritization of future AI initiatives.
  • Support alignment between technical development and operational objectives.
    

• Adoption, Enablement, and Documentation

• • Support onboarding and adoption of AI-enabled tools and workflows.
  • Develop documentation, user guides, training materials, and example usage patterns.
  • Contribute to internal best practices for effective and responsible AI utilization.
  • Document models, prompts, workflows, datasets, and evaluation results for transparency and reproducibility.

• Responsible AI and Governance

• • Follow RNGD’s AI ethical framework and standards for data privacy, security, and responsible use.
  • Identify and communicate risks, limitations, and unexpected model behaviors to leadership.
  • Support implementation of governance controls and AI operational safeguards.

Preferred Qualifications

• Bachelor’s degree in Computer Science, Data Science, Machine Learning, Engineering, Mathematics, or a related field, or equivalent practical experience.
• One to two years of professional, internship, or project-based experience developing software, data, or AI/ML solutions.
• Working proficiency in Python or similar programming languages and familiarity with ML libraries such as scikit-learn, PyTorch, Hugging Face, or LangChain.
• Experience working with large datasets and maintaining data integrity.
• Foundational understanding of APIs, version control (Git), cloud platforms, and data structures.
• Exposure to generative AI, large language models, embeddings, vector databases, graph data structures, or RAG workflows.
• Familiarity with cloud AI services such as Azure OpenAI, AWS Bedrock, or Google Vertex AI preferred.
• Experience with low-code platforms including Power Automate, Power Apps, or workflow automation tools preferred.
• Strong analytical, organizational, and problem-solving skills.
• Ability to communicate effectively with both technical and non-technical stakeholders.
• Demonstrated curiosity, initiative, and willingness to learn rapidly in evolving environments.

• Portfolio of AI projects, open-source contributions, coursework, or research preferred.

Core Competencies

• RNGD Values Alignment
  • Exemplifies RNGD’s core values:

• • • Renegade Mentality
    • Sweep Floors
    • Build Together
    • Honor Promises

• Technical Curiosity

• • Demonstrates strong interest in emerging AI technologies, tools, and workflows.
  • Continuously explores new methods to improve automation, intelligence, and operational efficiency.
  • Learns quickly and adapts to evolving technologies and platforms.

• Analytical Thinking

• • Uses logic, experimentation, and data to solve technical and operational problems.
  • Breaks down complex workflows into scalable AI and automation solutions.
  • Evaluates outputs critically to improve reliability and performance.

• Systems Thinking

• • Understands how systems, workflows, and data interact across the organization.
  • Builds solutions that align technical capabilities with operational needs.
  • Considers scalability, maintainability, and integration impacts in solution development.

• Problem Solving and Innovation

• • Approaches challenges with creativity and a solution-oriented mindset.
  • Develops practical AI-enabled solutions that drive measurable business value.
  • Identifies opportunities to improve workflows through automation and intelligent systems.

• Attention to Detail

• • Maintains accuracy and consistency in data, models, prompts, and workflows.
  • Documents technical work thoroughly and clearly.
  • Identifies issues, risks, and inconsistencies proactively.