Lead – Automation & AI Enablement

Job Tile: Lead – Automation & AI Enablement

Location: Kiambu County

Reporting to: Chief Transformation Officer / Chief Digital Officer

Function: Digital Transformation / Automation / Data & AI

Role Summary

The Lead – Automation & AI Enablement is responsible for designing, developing, and deploying automation, RPA, analytics, and AI/ML use cases across our client’s operations — from factory floors to support offices.

This is a hands-on technical role suited for a young, high-potential specialist with strong AI/ML and automation skills, capable of building prototypes, deploying real value-driven solutions, and supporting the digital transformation roadmap.

The ideal candidate brings a mix of software automation talent (Python, Power Automate, Automation anywhere), analytics dashboards (Power BI), and experience working around SAP environments (ECC or S/4HANA preferred).

Key Responsibilities

1. Automation & AI Roadmap Execution

• Support the creation and rollout of our client’s automation and AI enablement roadmap.

• Identify automation opportunities in production, supply chain, finance, HR, sales, and procurement.

• Prioritize high-impact use cases in collaboration with business stakeholders.

2. RPA & Workflow Automation

• Develop RPA bots using Automation Anywhere or Power Automate.

• Automate repetitive workflows across offices (finance, HR, procurement, logistics).

• Maintain automation scripts, troubleshoot failures, and optimize performance.

3. AI/ML & Predictive Insights

• Build machine learning models for forecasting (demand, raw material usage, supply chain).

• Support predictive maintenance and anomaly detection for production machines.

• Develop computer-vision models for quality control (optional but desirable).

• Validate model accuracy and deploy into live environments.

4. Systems Integration & SAP Ecosystem

• Integrate automation with SAP S/4HANA, SCADA, WMS, MIS, and ERP environments.

• Support creation of APIs, connectors, and data pipelines.

• Build process automation directly around SAP transactions where relevant.

5. Analytics & BI Enablement

• Build dashboards in Power BI or SAP BI (Bobj) for operational insights and KPI tracking.

• Automate data extraction, cleaning, and reporting pipelines.

• Enable business teams to make decisions using accurate, timely data.

6. Process Excellence & Governance

• Document automated workflows, models, and processes.

• Enforce automation governance standards, access control, and security.

• Track ROI, adoption, and tangible value created by each automation project.

7. Cross-Functional Collaboration

• Work with operations, production managers, finance teams, HR, supply chain, and commercial teams to identify automation and AI opportunities.

• Support change management and onboarding of end-users.

Ideal Candidate Profile

Qualifications

• Bachelor’s degree in IT, Computer Science, Data Science, Engineering, or related field.

• Certifications in RPA, Data Engineering, AI/ML, or Python are an advantage.

Experience (2–5 years)

• Hands-on development experience in:

o RPA: Automation Anywhere or Power Automate

o AI/ML: Python (Pandas, Scikit-learn, TensorFlow or PyTorch)

o Data engineering and analytics (SQL, Power BI)

• Experience in workflow automation, building bots, and deploying ML models.

• Exposure to SAP ECC or S/4HANA, or other ERP integration.

• Experience in manufacturing, FMCG, or supply chain environments is a plus.

Technical Skills

• Python: data wrangling, scripting, ML model development

• RPA: Automation Anywhere or Power Automate

• BI: Power BI, SQL, SAP BI

• Cloud: Azure or AWS fundamentals

• API/Integration experience

• Git, version control, automation testing

• Understanding of SCADA/WMS/ERP systems is an advantage

Soft Skills

• Strong analytical thinking and problem-solving

• Ability to translate business needs into technical solutions

• Curious, proactive, self-driven — “builder mindset”

• Excellent communication and stakeholder engagement

• Ability to work cross-functionally and handle multiple projects

What Success Looks Like

• 10–20 automation or AI use cases delivered within the first year.

• Measurable reduction of manual tasks, processing time, or error rates.

• Power BI and/or SAP BI dashboards adopted across functions for real-time insights.

• Predictive analytics applied to at least 2–3 business areas (maintenance, demand, finance).

• Strong stakeholder satisfaction and alignment with business priorities.

• Clear governance and documentation for all automation and AI assets.