Conduct deep-dive audits of existing workflows to dismantle bottlenecks, bridge data silos, and eliminate manual touchpoints.
Design and deploy "Agentic" workflows using LLM frameworks that can reason, utilize tools, and complete complex, multi-step tasks autonomously.
Connect AI agents with internal APIs, databases, and third-party SaaS platforms to ensure seamless data flow and action.
Implement feedback loops where AI agents report on their own performance, driving continuous refinement of process logic.
Design intuitive interfaces where human expertise can validate or steer agentic decisions.
Maintain rigorous documentation of both "analog" processes and "digital" agent logic to ensure security and compliance.

Proficiency in Six Sigma, Lean, or BPMN (Business Process Model and Notation). Experience in systems thinking and value stream mapping.
Experience with Python and LLM orchestration frameworks. Familiarity with Agentic patterns (Planning, Reflection, Tool Use).
Strong API integration skills (REST, GraphQL), version control (Git), and basic knowledge of cloud environments (AWS, Azure, or GCP).
Ability to work with SQL/NoSQL databases and structured/unstructured data parsing.
Bachelor’s or Master’s degree in Systems Engineering, Computer Science, Industrial Engineering, or a related technical field.
3+ years of experience in process optimization, with at least 1 year dedicated specifically to AI-driven automation.
The "Translator": You can talk to any department about their pain points and instantly translate those needs into technical requirements for an AI agent.
Resilient Problem-Solver: You have a natural curiosity for "breaking" processes to find more resilient ways to rebuild them.
Ethics-First Mindset: You understand the weight of autonomous automation and prioritize reliability, transparency, and ethical AI.

Process Systems Engineer – Agentic Automation

Key skills