Director, AI Engineering

Fifth Third Bank

. Creates and drives the strategy for business across artificial intelligence and machine learning systems that address diverse business challenges throughout the Bank.

Posted 5/1/2026full-timeCincinnati • North Carolina, Ohio, Texas • 🇺🇸 United StatesLeadWebsite

Tech Stack

Tools & technologies

AWSCloudDockerJavaScriptPythonPyTorchScikit-LearnSQLTerraform

About the role

Key responsibilities & impact

Creates and drives the strategy for business across artificial intelligence and machine learning systems that address diverse business challenges throughout the Bank.
Leads a team of AI Engineers who conduct rigorous data analysis, performing statistical evaluation, designing experimental frameworks, and developing algorithms that effectively leverage both structured and unstructured data.
Develops and implements AI and machine learning systems that address specific business challenges and deliver measurable value.
Creates and maintains model documentation, ensuring transparency in methodologies and approaches.
Researches, tests, and applies state-of-the-art generative AI models and/or solutions for potential use.
Develops agentic AI systems capable of autonomous reasoning, planning, and tool utilization for complex task completion.
Creates comprehensive evaluation frameworks to assess model performance, detect hallucinations, and ensure output quality.
Contributes to establishing best practices for AI development and deployment.
Develops and executes the AI portfolio strategy, overseeing budgets, vendor relationships, and talent planning to ensure alignment with business objectives and regulatory requirements.
Owns strategy and results for the AI function, interpreting organizational needs, recommending best practices, and ensuring alignment with business objectives and compliance requirements.
Extracts meaningful patterns and insights from complex, multi-dimensional data sets.
Applies advanced analytics including predictive modeling, machine learning, and optimization techniques.
Translates business questions into well-defined analytical problems with clear objectives.
Designs and executes experiments with statistically valid methodologies and evaluation criteria.
Develops specialized analytics for banking-specific use cases while maintaining compliance with financial regulations.
Manages large projects or teams, providing direct supervision to three or more professionals and overseeing area planning, prioritization, and execution.
Partners with cross-functional teams to understand business requirements and translate them into technical solutions.
Effectively communicates complex technical concepts to non-technical stakeholders.
Establishes and governs risk management, compliance frameworks, and value realization metrics for all AI initiatives, reporting outcomes to senior leadership and driving continuous improvement.
Presents findings, recommendations, and insights to business teams in accessible formats.
Collaborates with software engineers, cloud engineers, data engineers, and data scientists to integrate AI solutions into existing systems and products.
Works with compliance and security teams to ensure AI systems meet banking regulatory requirements.

Requirements

What you’ll need

Bachelor's degree in Computer Science, Statistics, Data Science, Mathematics, or related technical field; Advanced degree preferred but not required
8+ years of experience developing and deploying machine learning or AI solutions in production environments.
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.)
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
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.

Benefits

Comp & perks

health insurance
retirement plans
paid time off
flexible work arrangements
professional development
bonus pay
extensive benefits programs

ATS Keywords

✓ Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

PythonJavaScriptSQLgenerative AI techniquesmachine learning frameworksdeep learningneural networksmodel optimization techniquesAI orchestration frameworksdata visualization

Soft Skills

analytical thinkingproblem-solvingtime managementcommunication skillsself-motivatedteam leadershipcross-functional collaborationstorytellingprioritizationindependent work