Role: Forward Deployed Engineer (FDE) – Agentic AI & Multi-Agent Systems
Remote
Type: FTE – Full Time
Job Description
We are seeking a Forward Deployed Engineer (FDE) with strong expertise in Agentic AI, Multi-Agent Systems, Java, and Python to design, deploy, and optimize AI-powered business solutions. The ideal candidate will work closely with customers to understand business processes, identify automation opportunities, and implement scalable AI workflows leveraging RAG and agent orchestration frameworks.
Required Skills
· Strong programming experience in Python and Java.
· Hands-on experience with Agentic AI / Multi-Agent Systems.
· Expertise with agent orchestration frameworks such as LangGraph, CrewAI, or similar workflow platforms.
· Experience building autonomous workflows and AI agents with reliable API integrations.
· Strong understanding of Retrieval-Augmented Generation (RAG) and retrieval engineering.
· Experience implementing AI observability, monitoring, security guardrails, and governance controls.
· Ability to troubleshoot, test, and optimize AI agents based on business requirements and user feedback.
· Experience conducting workshops with business and technical stakeholders to identify AI automation opportunities.
· Strong knowledge of workflow automation, process transformation, and AI solution deployment.
Preferred Qualifications
· Experience in Accounting, Finance, or Close Management processes.
· Understanding of Month-End Close (MEC) and Year-End Close (YEC) business workflows.
· Customer-facing consulting or solution engineering experience.
· Experience deploying AI solutions in enterprise environments.
Key Responsibilities
· Design and implement Agentic AI and multi-agent workflows for enterprise customers.
· Build scalable AI solutions using RAG, LLMs, and orchestration frameworks.
· Lead discovery sessions and translate business processes into AI-driven solutions.
· Integrate AI agents with enterprise systems and APIs.
· Establish monitoring, security, and governance controls for AI applications.
· Collaborate with customer stakeholders to drive adoption and business value.
· Continuously refine AI agents and workflows based on feedback and performance metrics.
