AI Engineer – Agentic AI & Innovation

Location: Charlotte NC
Work Model: Hybrid Minimum 3 Days Onsite Per Week

A leading financial services organization is seeking a hands-on AI Engineer to join an Innovation & AI team focused on building and advancing next-generation Generative AI and Agentic AI solutions.

This is a highly technical hands-on role for an engineer who enjoys taking emerging business concepts and rapidly turning them into working prototypes. You will design intelligent agents AI-enabled applications and multi-step workflows that interact with enterprise data APIs metadata applications and analytical tools.

The ideal candidate brings strong Python and TypeScript development experience hands-on expertise with modern AI agent frameworks such as LangGraph and LangChain and experience collaborating within modern Git/GitHub-based development environments.

• Design and build Generative AI and Agentic AI prototypes proofs of concept and technical demonstrations
• Develop intelligent agents enterprise copilots and AI-enabled decision-support applications
• Build agentic workflows incorporating tool calling orchestration state management context engineering structured outputs and multi-step reasoning
• Develop Python services APIs tools automation and reusable AI components
• Build lightweight full-stack experiences to test new AI interaction models
• Integrate AI applications with enterprise data metadata APIs applications and analytical platforms
• Enable AI agents to reason across relationships between data assets systems business processes models controls and business concepts
• Evaluate LLMs agent frameworks orchestration approaches and context-engineering techniques
• Assess solutions based on reliability reasoning quality latency cost security and business value
• Work collaboratively within shared codebases using Git/GitHub and modern software development practices
• Document reusable engineering patterns technical constraints lessons learned and recommendations
• Partner with business architecture data cybersecurity risk and technology teams to help move successful prototypes toward enterprise adoption

• Hands-on experience building Generative AI Agentic AI machine learning or advanced software solutions
• Strong development experience with Python and TypeScript
• Experience building applications or intelligent agents powered by large language models (LLMs)
• Hands-on experience with LangGraph LangChain or comparable agent orchestration frameworks
• Experience with tool calling agent orchestration state management context engineering structured outputs and multi-step AI workflows
• Experience with Azure OpenAI or another enterprise AI platform
• Strong experience developing and integrating REST APIs and services
• Experience integrating AI applications with enterprise data applications APIs metadata or analytical tools
• Knowledge of SQL and structured/unstructured data
• Working knowledge of graph-based data structures knowledge graphs or metadata-driven applications
• Strong Git/GitHub experience and familiarity working collaboratively within shared codebases
• Ability to independently take an ambiguous or emerging business concept from idea to functioning prototype
• Ability to build modular documented testable and maintainable solutions
• Strong communication skills with the ability to explain technical decisions risks limitations and tradeoffs

• DataHub enterprise metadata platforms knowledge graphs graph databases or semantic data layers
• Multi-agent systems enterprise copilots or AI-enabled decision-support tools
• React JavaScript MongoDB or additional full-stack development experience
• Agent evaluation observability tracing guardrails human-in-the-loop workflows or AI cost monitoring
• Cloud-native development containerization CI/CD and automated deployments
• Experience working across multiple foundation models and evaluating model-selection tradeoffs
• GitHub Copilot or other AI-assisted software engineering tools
• Financial services Treasury liquidity funding forecasting risk or regulatory experience
• Responsible AI data governance cybersecurity model risk or enterprise technology controls

This role sits at the intersection of AI innovation and enterprise-scale financial technology. Rather than simply maintaining an established application youll have the opportunity to experiment with emerging AI capabilities build working solutions establish reusable engineering patterns and help shape how intelligent agents can be deployed within a complex enterprise environment.