AI Platform and internal model development
- Lead the design and development of an enterprise AI model using internal company data that delivers actionable insights and automated alerts.
- Build intelligent monitoring and exception-detection capabilities across SAP, ecommerce, IT security and other business applications.
- Establish scalable pipelines for continuous data ingestion, model training, evaluation and deployment.
Business Understanding & Problem Framing
- Engage closely with business teams to understand objectives, pain points, KPIs and decision workflows.
- Translate business requirements into structured AI/ML problems using strong analytical and consulting skills.
- Explore and analyse datasets to uncover hidden patterns and develop hypotheses that shape AI solutions.
Generative AI, NLP & LLM Development
- Lead development and deployment of Generative AI, NLP and LLM-based solutions tailored to business use cases.
- Build POCs and scalable solutions across functions such as operations, finance, supply chain, e-commerce, customer service and IT.
- Apply fine-tuning, prompt engineering, vector databases and domain-specific adaptation techniques.
Stakeholder Interaction
- Prepare and present solution proposals, models, dashboards and POCs to leadership and key stakeholders.
- Clearly articulate the impact and feasibility of AI solutions using storytelling and data-driven narratives.
- Demonstrate the relevance and effectiveness of Generative AI applications across multiple business domains.
Engineering, Cloud & MLOps Integration
- Integrate AI and ML models into enterprise systems across Azure, AWS, GCP or on-premise environments.
- Work closely with application, DevOps and IT teams to build robust MLOps pipelines ensuring automation, monitoring and lifecycle management.
- Oversee continuous improvement, productionisation and scaling of AI solutions.
