Location: Cincinnati, OH
Work type: Full-time
Compensation: DOE
Location: Cincinnati, OH
GENERAL FUNCTION:
This role involves conducting rigorous data analysis, performing statistical evaluation, designing experimental frameworks, and developing algorithms that effectively leverage both structured and unstructured data. The AI Engineer creates solutions that range from on demand analytics to fully integrated software systems, working closely with cross functional teams to align technical solutions with business requirements. Staying apprised and educating senior leaders on emerging AI trends, risks, and opportunities. Responsible and accountable for risk by openly exchanging ideas and opinions, elevating concerns, and personally following policies and procedures as defined. Accountable for always doing the right thing for customers and colleagues and ensures that actions and behaviors drive a positive customer experience. While operating within the bank's risk appetite, achieves results by consistently identifying, assessing, managing, monitoring, and reporting risks of all types.
ESSENTIAL DUTIES AND RESPONSIBILITIES:
AI Development and Implementation
Design, develop, and implement AI and machine learning systems that address specific business challenges and deliver measurable value. Create and maintain model documentation, ensuring transparency in methodologies and approaches. Research, test, and apply state of the art generative AI models and/or solutions for potential use. Develop agentic AI systems capable of autonomous reasoning, planning, and tool utilization for complex task completion. Create comprehensive evaluation frameworks to assess model performance, detect hallucinations, and ensure output quality. Stay current with emerging AI/ML technologies, frameworks, and methodologies. Contribute to establishing best practices for AI development and deployment. Sets enterprise wide technical standards by defining reference architectures, chairing design reviews, and approving model lifecycle gates (e.g., data sourcing, bias audits, drift monitoring).
Analytics and Insights
Extract meaningful patterns and insights from complex, multi dimensional data sets. Apply advanced analytics including predictive modeling, machine learning, and optimization techniques. Translate business questions into well defined analytical problems with clear objectives. Design and execute experiments with statistically valid methodologies and evaluation criteria. Develop specialized analytics for banking specific use cases while maintaining compliance with financial regulations.
Collaboration and Communication
Leads projects or processes with limited supervision, applying advanced knowledge to solve complex problems. Acts as a resource for colleagues, influencing technical direction and standards across multiple products or platforms. Drives cross team technical initiatives, ensuring integration, scalability, and compliance across multiple products and platforms. Partner with cross functional teams to understand business requirements and translate them into technical solutions. Effectively communicate complex technical concepts to non technical stakeholders. Present findings, recommendations, and insights to business teams in accessible formats. Collaborate with software engineers, cloud engineers, data engineers, and data scientists to integrate AI solutions into existing systems and products. Work with compliance and security teams to ensure AI systems meet banking regulatory requirements.
MINIMUM KNOWLEDGE, SKILLS AND ABILITIES REQUIRED:
Education and Experience
Bachelor's degree in Computer Science, Statistics, Data Science, Mathematics, or related technical field; Advanced degree preferred but not required. 6+ years of experience developing and deploying machine learning or AI solutions in production environments.
Technical Skills
Strong programming skills with proficiency in Python; familiarity with JavaScript and SQL. Expertise in generative AI techniques including prompt engineering, fine tuning, retrieval augmented generation (RAG), evaluation frameworks, tool integration, and agentic system design. Experience with cloud computing platforms (AWS preferred, specifically Bedrock, Sagemaker, Lex, etc.). Skilled in data visualization and storytelling, effectively communicating complex analytical insights in clear, actionable formats for technical and non technical audiences. Experience with machine learning frameworks (PyTorch, scikit learn, Hugging Face). Practical knowledge of deep learning, neural networks, and traditional ML algorithms. Familiarity with model optimization techniques including quantization and distillation. Knowledge of AI orchestration frameworks (LangChain, LlamaIndex, MCPs, etc.)
Engineering Practices
Proficiency with version control systems (Git/GitHub). Understanding of CI/CD pipelines and DevOps practices. Experience with containerization and Infrastructure as Code (Docker, Terraform). Knowledge of data structures, algorithms, and software design principles. Experience designing observability systems for AI applications.
Business and Soft Skills
Communicates clearly and builds consensus across teams. Mentors colleagues and promotes knowledge sharing. Excellent written and verbal communication skills. Strong analytical thinking and problem solving abilities. Ability to manage time effectively and prioritize competing demands. Self motivated with demonstrated capacity to work independently. Experience working in Agile environments. Proficiency with Microsoft Office suite (Word, Excel, PowerPoint). Understanding of ethical considerations in AI deployment.
Compensation: DOE