Lead – Automation & AI Enablement

Location:Thika
Function: Digital transformation /Automation/Data  & AI

Salary Range: 150,000 – 200,000 KES (depending on experience)

Industry: FMCG

Nationality: Locals

Role Summary

The Lead – Automation & AI Enablement will play a key role in accelerating the digital evolution.

The Lead – Automation & AI Enablement is responsible for designing, developing, and deploying automation, RPA, analytics, and AI/ML use cases across the company’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.

Key Responsibilities

1. Automation & AI Roadmap Execution

· Support the creation and rollout of the company’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.