Key Responsibilities

1.Process Mapping & Knowledge Design

Analyze, document, and optimize operational processes, SOPs, policies, and business rules.
Convert complex procedures into structured process maps, decision trees, workflow diagrams, and knowledge frameworks.
Design AI-ready process documentation that can be utilized by automation platforms, AI assistants, and Large Language Models (LLMs).
Identify process gaps, ambiguities, risks, and inefficiencies, and recommend improvements.

2. Low-Code / No-Code Workflow Development

Design and maintain workflows using low-code and no-code platforms.
Build process guidance tools, workflow applications, decision-support systems, and operational knowledge repositories.
Ensure workflows remain scalable, user-friendly, and aligned with evolving business requirements.
Collaborate with stakeholders to translate operational requirements into structured digital workflows.

3. AI Enablement & LLM Readiness

Structure operational knowledge and decision logic to support AI-assisted and LLM-driven workflows.
Develop frameworks that improve AI understanding of business processes, policies, and operational rules.
Support prompt design, workflow orchestration, and AI knowledge architecture initiatives.
Partner with business, operations, and technical teams to identify opportunities for AI adoption and intelligent automation.

4. AI Quality Assurance & Audit

Conduct audits and evaluations of AI-generated outputs, recommendations, and workflow decisions.
Validate AI performance against established SOPs, policies, and business requirements.
Develop testing methodologies, evaluation criteria, and quality standards for AI-assisted processes.
Monitor AI accuracy, consistency, hallucination risks, and adherence to operational guidelines.
Support human-in-the-loop review processes to continuously improve AI performance and reliability.

5. Governance, Monitoring & Continuous Improvement

Establish governance standards for process documentation, workflow design, and AI-enabled solutions.
Maintain version control and change management processes for SOPs, workflows, and AI knowledge assets.
Track operational and AI performance metrics, including accuracy, compliance, cycle time, adoption, and quality outcomes.
Produce reports, dashboards, and insights that communicate process effectiveness and AI performance to leadership.
Drive continuous improvement initiatives through data analysis, stakeholder feedback, and operational audits.

6. Stakeholder Collaboration

Partner with Operations, QA, Training, Product, Policy, and Technology teams to ensure process alignment.
Facilitate process discovery workshops and requirement-gathering sessions.
Support onboarding, training, and adoption of workflow tools and AI-enabled solutions.
Act as a subject matter expert on process intelligence, workflow optimization, and AI-enabled operations.

Required Qualifications

Bachelor's Degree in Computer Science, Information Systems, Engineering, Data Science, Business Analytics, Industrial Engineering, or a related field, or equivalent practical experience.
Minimum of 2-4 years of experience in Process Excellence, Business Process Management, Operations Excellence, Automation, Knowledge Management, or related disciplines.
Strong experience creating process maps, workflow diagrams, decision trees, and operational documentation.
Hands-on experience with low-code/no-code platforms, workflow tools, or business process management solutions.
Familiarity with AI technologies, LLMs, prompt engineering concepts, or AI-assisted workflows.
Strong analytical, problem-solving, and systems-thinking skills.
Excellent written, visual, and verbal communication skills.
Ability to simplify complex operational processes while maintaining accuracy and compliance.
Experience in e-commerce, logistics, customer support, returns and refunds, trust and safety, or operational excellence environments.
Experience working with AI-enabled products, conversational AI, knowledge systems, or intelligent automation solutions.
Familiarity with prompt engineering, AI evaluation frameworks, model testing, annotation workflows, or AI quality assurance methodologies.
Experience building dashboards, reports, and executive presentations.
Exposure to AI governance, model monitoring, or responsible AI practices.

Key Competencies

Process Intelligence - Ability to analyze, structure, and optimize complex operational workflows into scalable business processes.
AI & LLM Readiness - Understanding of how AI systems consume, interpret, and execute structured knowledge and decision logic.
Workflow & Systems Thinking - Ability to design interconnected workflows, decision frameworks, and operational ecosystems.
Quality & Governance - Strong focus on accuracy, compliance, auditability, and continuous improvement.
Data-Driven Decision Making - Ability to leverage operational metrics, audits, and insights to improve processes and AI performance.
Cross-Functional Collaboration - Strong stakeholder management skills with the ability to influence across operations, business, and technology teams.
Communication & Documentation - Ability to communicate complex concepts clearly through process maps, documentation, presentations, and visual frameworks.

Process Intelligence & AI Enablement Specialist - Return & Refund