Responsibilities
- AI Use Cases & Automation Delivery
- Identify and prioritize AI/automation opportunities, map current vs. future processes, and define clear business requirements across functions (e.g., exception handling, document processing, service operations, billing/audit, reporting)
- Develop and configure AI prototypes/solutions using modern AI tools and platforms (e.g., LLM apps/agents, RAG, document processing), then iterate into production-ready delivery with internal IT/engineering teams
- Help identify where workflow automation/low-code tools can streamline processes (e.g., approvals, data analysis, exception management) and support requirement definition, testing, and rollout
- Hands-on build automations where appropriate; validate solution quality through testing and UAT support with clear documentation
- Apply AI for document processing, data extraction, classification, decision support, and workflow optimization; ensure solutions are measurable (cycle time, accuracy, cost savings)
- Run discovery with business stakeholders, design, build, and ship AI-powered applications end-to-end — from prototype to production
- Ensure responsible AI and operational readiness: data privacy, access control, auditability, monitoring, and clear handover/support procedures
System Integration (Enterprise Applications & Data)
- Build and maintain system integrations between AI solutions and enterprise systems (e.g. finance/accounting platforms, and—where applicable—TMS/WMS etc.) via APIs, files, or EDI
- Work with internal IT/security teams to ensure appropriate access control, data privacy, and compliance requirements are met for each solution
Cloud, Data & AI Platform Skills
- Familiarity with cloud and AI platforms used to deliver enterprise solutions (Azure preferred; other major clouds are a plus)
- Familiarity with low-code/workflow tools (e.g., Power Platform); ability to translate business needs into configurable solutions matters most
Collaboration, Training & Change Management
- Partner with business team to identify opportunities and prioritize AI/automation backlog based on business value
- Create and maintain technical documentation, SOPs, and user guides; ensure solutions are supportable.
- Run knowledge-transfer and training sessions to drive adoption; communicate changes and collect feedback for continuous improvement
Requirements
- Solid understanding of AI/LLM concepts and practical application (prompting, grounding, evaluation, and limitations)
- Solid technical skills to support development and troubleshooting (e.g., Cloud, Coding, SQL, API concepts)
- Ability to build AI solutions and automations (prototype to small production use cases) using modern, best-fit tools/platforms; comfortable learning new AI tools quickly
- Understanding of data and integrations (e.g., files/CSV, APIs) is; deeper technical skills can be learned on the job
- Awareness of security and access concepts (e.g., permissions, roles) is a plus
- Comfortably working with business and IT teams in an enterprise environment; exposure to cloud-based solutions is a plus
- Understanding of logistics and finance processes is a strong plus (helps translate operational needs into scalable automations)
- Data literacy: ability to work with structured data, understand KPIs, and validate outputs; Power BI/SQL is a plus
- Logistics experience is a plus, but learning ability and attitude are more important than full expertise
Learning & Ownership Expectations (Important)
- Self-learner with strong willingness to learn AI, automation, and cloud technologies
- Able to learn from documentation, examples, and hands-on practice
- Take responsibility for assigned tasks and follows through to completion
- Proactively asks questions when unsure instead of waiting passively
- Willing to improve solutions based on feedback and lessons learned
Education & Experience
- Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science , Information Systems, Supply Chain, or a related field (or equivalent practical experience)
- 2-5 years of relevant experience (internships, graduate programs, or project experience in AI, process improvement, automation, analytics, or related areas are welcome)
If you have the energy and qualifications to add to our velocity, Please visit KLN Company Webpage to apply or send your CV with your pr