AI Engineer - Hybrid

Genesis
10 is currently seeking an AI Engineer for a hybrid position with a Global Financial Institution located in Charlotte, NC. This is a 24+ month contract opportunity.

The Innovation & AI team is seeking a hands-on AI Engineer to rapidly prototype and advance next-generation AI capabilities for Treasury. The primary focus is innovation: translating business opportunities into working solutions, testing emerging technologies, and establishing reusable patterns. This role will develop intelligent agents and AI-enabled experiences that reason across Treasury data, metadata, business processes, and analytical tools. This is a hybrid role requiring a minimum of 3 days per week on-site.

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 Data Hub-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

Requirements:

• 5+ years of Finance experience, or equivalent demonstrated through one or a combination of the following: work or consulting experience, training, military experience, education
• Demonstrated experience building generative AI, agentic AI, machine learning, or advanced software solutions
• Strong hands-on Python and Type Script 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 Lang Graph, Lang Chain, 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

Desired skills:

• Experience with Data Hub, 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, Type Script, 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…