AI Process Automation ​/ Agentic Workflow Engineer & Coach IRC301639

AI Process Automation / Agentic Workflow Engineer & Coach IRC
301639

Function:
General Artificial Intelligence

Experience:

10-15 years

Location:

Poland

Skills:

Agentic & Multi-Agent Systems, AI Governance, AI-Powered Low-Code, Area Optimization, BPMN 2.0, Business Process Modeling, LLM

• Company-Wide AI-First transformation:
  This is not a simple pilot project or an isolated experiment. The company is undergoing a massive reorganization of how work gets done.
• Paradigm shift (Agentic Workflows):
  The goal is NOT to use AI as a productivity add-on (e.g., an email writer or drafting assistant), but to have AI agents execute core work while humans shift to managing and governing those processes.
• Duration, format, and engagement model:
  Duration: 6–9 months (a medium-to-long-term engagement focused on sustainability, not a quick, surface-level delivery). Embedded Operating Model:
  Engineers will not work in isolation within an IT or R&D department. They will be embedded directly inside functional business units (Finance, HR, Marketing, Operations, etc.), working side-by-side with process owners. Non-SDLC scope:
  This project has no connection to traditional software engineering (Software Development Life Cycle). It focuses exclusively on operational business workflows outside of IT.
• Team architecture & collaboration model:
  The project relies on a paired team model (Engineer + Champion). 1-on-1 Pairing:
  Each engineer will be paired directly with a designated “AI Champion”—a business-side Subject Matter Expert (SME) owning their function’s use cases. Mentorship & coaching:
  The AI Champion will be undergoing parallel training. The engineer’s role is to coach them on live, real-world use cases, taking them from early-stage adoption to full autonomy.
• Tech stack & design philosophy:
  Technology Ecosystem:
  The project is anchored primarily in Claude (Anthropic)—its models, ecosystem, and agent orchestration capabilities. Design philosophy:
  Complete Re orchestration (As-Is to To-Be):
  Rather than taking an existing process and “bolting” AI onto the end, the workflow is deconstructed and rebuilt from scratch. Clear task delegation:
  Precise definition of what work is delegated to agents versus what is retained for human oversight (Human-in-the-Loop).
• Ultimate success metric (Primary KPI):
  Enablement & Self-Sufficiency:
  This is explicitly NOT a “build-and-walk-away” engagement. Success is not measured merely by shipping functional code or workflow builds. The real benchmark:
  Success is measured by what the AI Champion can independently do (extend, troubleshoot, and evolve the workflow) at the end of the engagement without the engineer’s help.
• Human & cultural challenges (Change Management):
  Skepticism and Fear:
  The client explicitly notes that non-technical business owners may be unfamiliar with, wary of,or hesitant about agentic AI (fear of job displacement, lack of trust in agents). Critical Need for high EQ:
  The project’s success hinges just as much on the engineer’s interpersonal skills (empathy, patience, coaching, trust-building) as it does on their technical prompt engineering or agent architecture skills.

#LI-OM1

AI-First & Agentic workflows experience:
Proven experience designing and implementing AI agent-based workflows (specifically within the Claude / Anthropic ecosystem or similar orchestration platforms).

Business process re-engineering:
Demonstrated ability to map as-is manual/semi-automated business processes and redesign them from scratch into AI-first operating models (rather than just adding AI as a productivity plugin).

Coaching & mentorship track record:
Experience training and upskilling non-technical business users (ability to teach, shadow, and effectively transfer knowledge).

Business experience & stakeholder management:
Experience working directly with functional business stakeholders outside of IT/Software Engineering (e.g., Finance, HR, Operations, Marketing, Legal).

High emotional intelligence (EQ):
Exceptional ability to build trust, manage change, and overcome reluctance or fear from stakeholders skeptical about agentic AI.

Engagement availability:
Ability to commit to a 6–9 month embedded…