AI Strategy & Solution Delivery
- Design and implement AI-driven solutions that improve operational efficiency and decision-making across departments.
- Translate business use cases into scalable AI and automation architectures.
- Contribute to the AI and automation roadmap in collaboration with the Applications, AI and Automation Director.
Workflow Automation
- Develop and maintain enterprise automations using low-code and API-based tools (e.g., Power Automate or similar platforms).
- Integrate automation workflows with ERP systems, internal applications, collaboration platforms, and data sources.
- Establish standards for automation lifecycle management, monitoring, and performance optimization.
Enterprise RAG (Retrieval-Augmented Generation)
- Design and deploy enterprise knowledge assistants using RAG architectures.
- Integrate structured and unstructured data sources into secure retrieval pipelines.
- Implement evaluation frameworks to measure response quality, accuracy, and performance.
- Ensure proper access controls and data security in AI knowledge systems.
Intelligent Agents & AI Applications
- Develop and deploy AI agents to support business processes, operational inquiries, and decision support.
- Integrate agents with enterprise systems through secure APIs and workflows.
- Monitor agent performance and continuously refine prompts, orchestration, and retrieval logic.
Predictive Analytics & Machine Learning
- Collaborate with the BI and data warehouse teams to develop predictive models leveraging enterprise data.
- Apply machine learning techniques to generate forecasting, trend analysis, and operational insights.
- Deploy models into production workflows and dashboards where appropriate.
- Partner with business stakeholders to validate and interpret predictive outputs.
Governance, Security & Responsible AI
- Ensure AI solutions align with enterprise data governance, DLP policies, and cybersecurity standards.
- Implement logging, monitoring, and auditability within AI and automation solutions.
- Support risk assessments for new AI use cases and integrations.
- Promote responsible and ethical AI usage across the organization.
Collaboration & Stakeholder Engagement
- Work closely with global business teams to identify high-value automation and AI opportunities.
- Support structured intake and prioritization of AI and automation requests.
- Provide guidance and training to stakeholders on AI capabilities and limitations.
Education
- Bachelor's or master's degree in computer science, Data Science, Engineering, Information Systems, or related field.
Required Experience
- 5+ years of experience in automation, AI development, machine learning, or related technical roles.
- Hands-on experience with workflow automation platforms (e.g., Power Automate, UiPath, or similar).
- Experience designing and implementing AI/ML solutions in production environments.
- Familiarity with large language models (LLMs), prompt engineering, and RAG architectures.
- Experience integrating AI solutions with enterprise systems via APIs.
Technical Skills
- Proficiency in Python or similar programming language for AI/ML development.
- Experience with ML libraries and frameworks (e.g., scikit-learn, TensorFlow, PyTorch, or similar).
- Understanding of data warehousing and BI systems.
- Strong knowledge of REST APIs and system integrations.
- Familiarity with cloud platforms (e.g., Azure, AWS, or similar).
Preferred Qualifications
- Experience deploying enterprise AI solutions in manufacturing, ERP-driven, or operational environments.
- Familiarity with model monitoring, evaluation frameworks, and MLOps concepts.
- Exposure to data governance and security best practices in AI systems.
