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 (. Copilot, Power Automate, Microsoft Fabric, .
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 (. 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 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 (. 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 (. 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.