to be responsible for building and productionizing advanced AI systems powered by LLMs and intelligent agents. Your work will focus on internal enablement, building AI systems that help consultants and bankers. This will help accelerate research, improve information discovery, relevance across existing systems, and streamline workflows as part of the firm’s digital transformation strategy.
Check out the role overview below If you are confident you have got the right skills and experience, apply today.
This role is 80% technical build, integration, and delivery, and 20% on stakeholder alignment, design documentation, and iterative discovery.
Location:
Tampa, FL or Raleigh, NC (2-3 days/week)
Salary:
up to 150k base + bonus
Visa sponsorship is NOT AVAILABLE
Responsibilities:
• Build multi-agent systems that can reason, plan, and execute internal workflows such as financial modeling support, market research synthesis, and document preparation.
• Develop systems that can remember context and prior steps so employees can work through complex, multi-step requests without having to repeat information.
• Design and implement backend infrastructure that supports AI assistants, internal chatbots, and workflow agents.
• Develop conversational knowledge assistants, semantic search features, and document drafting tools that improve discovery and relevance of proprietary research and data
• Design and deploy production-ready LLM workflows that deliver reliability, accuracy, and scalability, maintaining clear documentation and communication for internal teams
• Develop and orchestrate AI agents that chain LLM calls, manage context, and integrate with FMI’s platforms (Salesforce, DealCloud, NetSuite, HubSpot, Box).
• Advance prompt-engineering and optimization strategies to balance cost, accuracy, and performance across use cases.
• Build and manage API’s that connect AI capabilities with infrastructure, knowledge bases, document repositories and data systems.
• Implement evaluation frameworks, monitoring, and A/B testing to ensure workflow consistency, reliability, and safety.
• Create visible improvements in efficiency, reduction in search and rework time through AI-enabled workflows.
Requirements:
• Bachelor’s degree in Computer Science, Data Science, or related
• 2+ years of software engineering experience with production systems (preferably in automation, AI, or data-intensive environments)
• Demonstrated experience delivering production-grade LLM applications, hands-on build and deployment work beyond prototypes
• Experience building multi-step AI agents, LLM chaining, and workflow automation
• Expertise in prompt engineering and optimization techniques
• Experience building and integrating APIs across enterprise systems (Box, Salesforce, DealCloud, NetSuite, HubSpot)
• Familiarity with distributed architectures, vector databases, and data pipelines supporting AI agent workflows. xsgimln
• Ability to author and maintain Product Requirements Documents (PRDs) defining agent logic, workflow steps, and success metrics.
• Experience deploying and managing models or AI services in AWS (or Azure/GCP)