AI Implementation Expert
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.
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