AI Engineer, Innovation & AI

Description

Title:AI Engineer, Innovation & AI

Location: Charlotte, NC

Duration: 12 months

Work Engagement: W2

Work Schedule: Hybrid 3 days in office/2 days remote

Benefits on offer for this contract position: Health Insurance, Life insurance, 401K and Voluntary Benefits

Summary:

In this contingent resource assignment, you may: Consult on complex initiatives with broad impact and large-scale planning for Finance. Review and analyze complex multi-faceted, larger scale or longer-term Finance challenges that require in-depth evaluation of multiple factors including intangibles or unprecedented factors. Contribute to the resolution of complex and multi-faceted situations requiring solid understanding of the function, policies, procedures, and compliance requirements that meet deliverables. Strategically collaborate and consult with client personnel. Required Qualifications: Finance experience, or equivalent demonstrated through one or a combination of the following: work or consulting experience, training, military experience, education.

Key Responsibilities:

• Rapidly design and build AI prototypes, proofs of concept, and technical demonstrations for Treasury use cases.
• Partner with Treasury users to identify high-value opportunities and translate complex business problems into testable solutions.
• Develop context-aware agents, enterprise copilots, and AI-enabled decision-support experiences.
• Build agentic workflows that plan, reason, use tools, maintain state, coordinate specialized capabilities, and incorporate human oversight when appropriate.
• Integrate agents with a DataHub-based graph context layer that provides governed business, technical, operational, and data context.
• Enable agents to navigate relationships across data assets, metadata, systems, models, processes, controls, and business concepts.
• Develop Python services, APIs, tools, and reusable components that connect AI capabilities with enterprise applications and data platforms.
• Create lightweight full-stack experiences to test new interaction models with business users.
• Evaluate models, agent frameworks, context-engineering techniques, and orchestration patterns based on intelligence, reliability, latency, cost, security, and business fit.
• Define prototype success measures and evaluate reasoning quality, contextual accuracy, tool execution, user value, and operational reliability.
• Document architectural patterns, lessons learned, technical constraints, and recommendations for further investment or production maturation.
• Collaborate with architecture, data, cybersecurity, risk, and control partners to establish a viable path from experimentation to governed enterprise adoption.
• Develop reusable engineering patterns that accelerate future AI delivery across Treasury.

Key Requirements:

· Applicants must be authorized to work for ANY employer in the U.S. This position is not eligible for visa sponsorship.

• Demonstrated experience building generative AI, agentic AI, machine learning, or advanced software solutions.
• Strong hands-on Python and TypeScript development skills, including APIs, services, automation, testing, and debugging.
• Experience developing intelligent agents or applications powered by large language models.
• Hands-on experience with tool calling, agent orchestration, state management, context engineering, structured outputs, and multi-step reasoning workflows.
• Experience with LangGraph, LangChain, or comparable agent orchestration technologies.
• Experience with Azure OpenAI or another enterprise AI platform.
• Experience integrating AI applications with enterprise data, metadata, APIs, applications, and analytical tools.
• Working knowledge of graph-based data structures, metadata-driven applications, or knowledge graph concepts.
• Strong understanding of REST APIs, SQL, structured and unstructured data, Git, and modern software development practices.
• Ability to independently move from an emerging business concept to a functioning prototype.
• Ability to operate effectively in an exploratory environment while producing modular, documented, and maintainable solutions.
• Strong communication skills and the ability to explain technical decisions, limitations, risks, and tradeoffs to business and technology stakeholders.

Nice-to-Have Skills and Experience
• Experience with DataHub, enterprise metadata platforms, knowledge graphs, graph databases, or semantic data layers.
• Experience building multi-agent systems, enterprise copilots, or AI-enabled decision-support applications.
• Full-stack development experience with React, TypeScript, JavaScript, MongoDB, or comparable technologies.
• Experience with agent evaluation, observability, tracing, guardrails, human oversight, and cost monitoring.
• Experience designing AI experiences that dynamically select and use enterprise tools, data, and specialized capabilities.
• Experience with cloud-native development, containerization, CI/CD, and automated deployment.
• Familiarity with multiple foundation-model families and model-selection tradeoffs.
• Experience using GitHub Copilot or other AI-assisted engineering tools.
• Financial services, Treasury, liquidity, funding, forecasting, risk, or regulatory experience.
• Familiarity with responsible AI, data governance, cybersecurity, model risk, and enterprise technology controls.