Job Description

aculocity

Aculocity is the technology and data company within the GVW Group, serving as the digital backbone for our operating companies, including Autocar, Autocar Parts and Triz Engineering. We deliver enterprise-grade software and systems, analytics, and AI solutions that power innovation in the automotive manufacturing and commercial vehicle industries.
Our teams collaborate closely with business leaders to turn data, AI, and automation into measurable business value across our operating companies and global operations. With teams based in the United States and South Africa, Aculocity combines deep industry expertise with cutting-edge technology to drive real-world transformation,

Summary:

The

AI Implementation Expert

is a hands-on practitioner who turns AI opportunities into operational business value.
You will identify opportunities for automation, decision support, and efficiency improvement using AI tools, and then

design, prototype, and deploy quick-win AI solutions

, ranging from generative AI copilots and chatbots to lightweight predictive models. This role combines

business analysis

,

AI prototyping

, and

AI/ML implementation

skills, helping teams experience tangible value from AI without lengthy development cycles.
Your mission: make AI real for our Centers of Excellence - fast, safe, and scalable.

Key Responsibilities:

Business Discovery and Solution Design

Engage with business stakeholders to

identify opportunities

, pain points, inefficiencies, or knowledge gaps where AI can deliver measurable improvement. Translate business needs into

well-defined AI use cases

with measurable outcomes and clear ROI. Evaluate

feasibility and align initiatives

with Aculocity's data and AI strategy. Draft

high-level solution designs,

including model inputs, outputs, and integration points with existing systems (e.g. Copilot, Power Automate, Microsoft Fabric, etc.).

AI Solution Prototyping and Implementation

Design

end-to-end AI workflows

, from data inputs and prompts to integration points with existing systems

Build and deploy rapid AI Solutions

using tools such as Azure OpenAI, Microsoft Copilot, ChatGPT, or similar frameworks.

Design and test conversational agents and copilots

that integrate into business workflows. Develop and deploy

RAG (retrieval-augmented generation)

and prompt-engineered copilots embedded into business workflows. Build and operationalize small to medium-scale

ML models

(e.g. classification, forecasting, anomaly detection) using tools like Python, Fabric ML, or Azure ML.

Integrate AI solutions

with existing data sources, APIs, and business systems. Implement

monitoring and continuous improvement

through prompt tuning, retraining, and user feedback.

Evaluation, Governance and Adoption

Define success metrics and evaluate ROI or

business impact

of implemented AI solutions. Ensure ethical, secure, and responsible AI deployment aligned to

corporate governance standards

. Promote

secure, auditable, and compliant AI usage

through versioning, logging, and human-in-the-loop controls. Support

training, change management and AI literacy programs

to drive adoption within business teams.

Document

solutions, maintain prompt libraries, and promote reusable patterns.

Requirements

Education:

Degree in Data Science, Computer Science, Engineering, or related discipline (master's or PhD a plus.)

Qualifications and certifications are preferred but not mandatory - it's all about your ability to execute!

Certification in Microsoft Power Platform, Azure AI, or Applied Data Science a plus.

Experience:

Demonstrated track record of delivering applied AI, analytics, or automation solutions that created measurable business impact. Experience in AI product development, business analysis, or technical consulting. Experience in manufacturing, supply chain, or service operations a plus.

Skills:

Technical Skills

Proficiency with

generative AI tools and frameworks

(e.g. ChatGPT, Azure OpenAI, Power Automate, Copilot Studio). Experience designing, configuring, or

deploying AI Agents and Copilots

to automate business processes or enhance user productivity. Experience with

Python, SQL, and standard data science / ML libraries

(e.g. pandas, scikit-learn, Azure ML). Familiarity with

Power BI, Microsoft Fabric

, or similar data platforms. Understanding of

REST APIs

, connectors, and integration methods. Working knowledge

of ML lifecycle

concepts, including data prep, training, evaluation, deployment.

Business & Communication Skills

Strong analytical and problem-solving mindset. Ability to engage with business users, run workshops, and elicit requirements. Ability to translate technical outcomes into business value language. Experience preparing solution proposals and ROI assessments.

Mindset

We're looking for someone who:Experiments with emerging AI tools but always grounds ideas in business value. Thinks like an engineer but communicates like a consultant. * Sees AI not as a buzzword, but as a systematic enabler of smarter work.