AI Engineer, Innovation & AI (contract)

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.