Agentic AI Forward-Deployed Engineer

What you'll do

• Map and document existing workflows, data flows, and exception paths by embedding with program teams.
• Produce automation roadmaps that prioritize high-volume workflows based on expected value and risk.
• Design, build, and deploy AI agents that reason and act across existing tools and APIs.
• Develop evaluation frameworks, golden datasets, and regression tests to validate non-deterministic agent behavior.
• Instrument agents with audit trails, monitoring, and metrics to track value and risk reduction.
• Drive adoption and change management by training the workforce and redesigning roles around automation supervision.
• Codify field learnings into reusable playbooks, components, and shared capabilities for the broader organization.

What we're looking for

• 5+ years of experience in software engineering, machine learning engineering, technical advisory, or solutions engineering roles.
• 2+ years of experience building applications with generative and agentic AI technologies, including LLMs, RAG, MCP, or multi-agent orchestration.
• Experience developing production code in Python or TypeScript.
• Experience deploying an LLM-powered system or AI agent into a production environment, including evaluation, monitoring, and iteration.
• Experience integrating with enterprise systems and data sources such as ERP, CRM, ITSM, or SharePoint.
• Experience working with customers or business stakeholders to elicit requirements, map processes, and guide technology adoption.
• Ability to obtain a Secret clearance.
• Experience with agentic coding and orchestration tools such as LangGraph or OpenAI Agents SDK (preferred).
• Experience in a forward deployed, embedded, or residency-style engineering role at a customer site (preferred).
• Experience with organizational change management, training, or workforce transition programs (preferred).
• Experience with business process analysis, BPMN, or value stream mapping (preferred).
• Experience with cloud platforms and containerized deployment including AWS, Azure, Kubernetes, or Terraform (preferred).
• Master's degree (preferred).
• Secret clearance (preferred).