Lead AI Engineer

Summary As the Lead AI Engineer at Rialto Capital, you will work closely with the Director of Information Engineering & AI to develop and implement cutting-edge AI solutions. Your role will be central to advancing our AI capabilities and delivering enterprise-scale solutions that drive real business impact. You will leverage your expertise in machine learning, deep learning, and large language models (LLMs) to architect and operationalize AI systems that enhance Rialto’s data-driven insights, automate key business processes, and improve overall decision-making in the commercial real estate domain. Key Responsibilities

Machine Learning & Deep Learning Innovation

• Design, train, and deploy ML models across various business functions.
• Utilize supervised, unsupervised, and reinforcement learning techniques to address a wide range of use cases.
• Collaborate with cross-functional teams to identify critical business problems and propose data-driven solutions.
  
  

Conversational AI & Large Language Models (LLMs)

• Develop, fine-tune, and deploy enterprise-level LLMs (e.g., GPT, Ollama, Groq) for both internal and client-facing solutions.
• Implement Retrieval-Augmented Generation (RAG) and dialogue management systems to enable dynamic, context-aware conversational experiences.
• Drive initiatives in prompt engineering, model optimization, and response quality improvements.
  
  

Enterprise-Level API Development & Integration

• Architect and implement RESTful APIs and microservices to connect AI models with internal and external systems.
• Collaborate with the IT team to ensure secure, scalable, and compliant data exchange practices.
• Work closely with DevOps to streamline CI/CD pipelines for seamless deployment of AI services.
  
  

Data Engineering & Governance

• Partner with Data Analysts and Data Engineers to design robust data pipelines using tools such as Apache Spark, Airflow, or similar.
• Oversee data preprocessing, feature engineering, and data wrangling to ensure high-quality input for AI models.
• Ensure alignment with the organization’s data governance policies, maintaining data security and compliance standards.
  
  

Technical Leadership & Mentorship

• Lead a small team of AI engineers and Data Scientists, providing guidance, code reviews, and best practices for ML/DL development.
• Facilitate knowledge sharing and collaboration through regular team meetings, workshops, and training sessions.
• Partner with cross-functional leaders (e.g., CIO, Data Analysts, Product Managers) to align AI initiatives with Rialto’s strategic goals.
  
  

Continuous Improvement & Collaboration

• Stay current on emerging AI trends, tools, and frameworks, evaluating their potential business impact.
• Propose and champion innovative projects that leverage generative AI to transform Rialto’s business processes.
• Work with the Director of Information Engineering & AI to track key metrics (e.g., model performance, ROI) and report progress to stakeholders.
  
  

Qualifications

• Education & Experience
• Bachelor’s degree required in computer science, Engineering, or a related field preferred; Master’s or Ph.D. highly preferred.
• 5 years of professional experience developing AI/ML solutions, with a strong track record of successful enterprise deployments.
• Experience in financial services or real estate industries is a plus.
• Technical Expertise
• Proficiency in Python and deep learning frameworks such as TensorFlow, PyTorch, and related libraries (e.g., Hugging Face Transformers).
• Hands-on experience with LLMs, prompt engineering, and techniques for fine-tuning large-scale language models.
• Experience with data engineering tools like SQL, Apache Spark, Airflow, and data pipeline orchestration.
• Systems & Tools
• Familiarity with Azure cloud services (e.g., Azure Machine Learning, Data Factory) or equivalent cloud platforms.
• Experience with containerization (Docker, Kubernetes) and CI/CD best practices for scalable deployments.
• Solid understanding of version control systems (Git) and collaborative development workflows.
• Soft Skills
• Excellent communication skills to translate complex AI concepts into actionable insights for business stakeholders.
• Strong leadership, project management, and problem-solving abilities.
• Collaborative mindset with the ability to work across multifunctional teams and drive successful outcomes.