SENIOR AI ENGINEER- Financial Data & Agentic AI

Porce Consulting Services LLC is seeking a Senior AI Engineer to support financial data and Agentic AI initiatives. The role focuses on integrating enterprise financial data and EPM systems with production-grade AI agents, including multi-agent orchestration, lifecycle controls, guardrails, monitoring, and human-in-the-loop workflows.

Responsibilities:

• Query, structure, transform, and integrate enterprise financial data across SQL databases and EPM systems
• Design reliable data pipelines and data access patterns for financial applications and AI-powered workflows
• Work with complex financial data including budgeting, forecasting, planning, reporting, revenue, expenses, and other enterprise financial datasets
• Ensure financial data is accurate, consistent, secure, and accessible to AI applications and agents
• Collaborate with finance and data teams to understand complex financial logic and translate business requirements into technical solutions
• Design, develop, and scale production-grade AI agents for high-volume financial workflows
• Build AI systems capable of retrieving, analyzing, reasoning over, and acting on enterprise financial data
• Develop solutions optimized for accuracy, performance, latency, scalability, compliance, and auditability
• Integrate AI agents with databases, enterprise applications, APIs, data platforms, and other business tools
• Implement appropriate monitoring, evaluation, logging, and observability for AI agent performance and reliability
• Design and implement multi-agent architectures using supervisor-worker and hierarchical agent patterns
• Build systems that decompose complex financial problems into smaller tasks handled by specialized sub-agents
• Implement intelligent routing of tasks to the appropriate sub-agent based on the problem, context, and required expertise
• Design context-isolated workflows to ensure agents receive only the information required to complete their assigned tasks
• Coordinate multiple agents and tools to support complex financial analysis and decision-making workflows
• Build tool-augmented AI agents capable of interacting with databases, APIs, enterprise applications, and other systems
• Implement agent lifecycle controls, including event callbacks, pre-processing and post-processing hooks, and state management
• Design mechanisms for agent state persistence, memory, workflow recovery, and execution tracking
• Implement deterministic guardrails to control agent behavior and prevent unauthorized or incorrect actions
• Build human-in-the-loop workflows for high-risk, sensitive, or approval-based financial activities
• Ensure agent actions and outputs are traceable, explainable, and auditable