The organization is looking to advance both traditional and Generative AI capabilities to drive business innovation, operational efficiency, and digital transformation by converting complex problems into AI-enabled solutions that provide measurable value.
Requirements
- Proven experience designing and implementing end-to-end AI/ML workflows using Python, TensorFlow, PyTorch, Scikit-learn, or equivalent.
- Demonstrated ability to apply AI to structured and unstructured data sources, including text, images, and time series data.
- Strong expertise in cloud-based machine learning platforms (e.g., Azure ML, AWS SageMaker, Google Vertex AI).
- Familiarity with data engineering and storage technologies including SQL, Spark, Delta Lake, and cloud-based data lakes.
- Experience with MLOps practices, including automated model training, deployment pipelines, and model monitoring.
- Experience deploying large language models (LLMs), computer vision models, or generative AI technologies in enterprise settings.
- Hands-on knowledge of vector databases, embedding models, and prompt engineering for retrieval-augmented generation (RAG) systems.
Responsibilities
- Lead the strategic vision and execution of enterprise-wide AI initiatives, ensuring alignment with organizational goals and digital transformation objectives.
- Collaborate with cross-functional teams to embed AI solutions into enterprise data workflows, ensuring models are well-governed, scalable, and deliver measurable business value by streamlining operations, improving decision-making, and unlocking actionable insights.
- Lead the design, development, and deployment of AI/ML solutions to support business functions such as forecasting, anomaly detection, computer vision, and natural language understanding.
- Lead the design, development and deployment of GenAI solutions using large language models (LLMs), image generation models, and retrieval-augmented generation (RAG) architectures for applications such as summarization, content generation, and intelligent automation.
- Analyze and communicate AI model results and accuracy in a way that is accessible to non-technical stakeholders, ensuring transparency and informed decision-making.
- Develop, lead, and continuously refine the organization's Generative AI (GenAI) strategy, identifying high-impact use cases and enabling enterprise-wide adoption.
- Partner with internal teams to embed GenAI into business processes, tools, and platforms to improve decision-making, customer engagement, and operational workflows.
Other
- Ability to influence direction and adoption of AI solutions through strong collaboration and delivery leadership.
- Ability to translate business requirements into AI solutions with measurable ROI and clear KPIs with accountability for driving value realization.
- Excellent communication skills and the ability to articulate complex technical concepts to both technical and non-technical audiences.
- Strong project management skills and experience delivering AI solutions from proof-of-concept through production.
- Experience working in Agile/Scrum environments and collaborating across multidisciplinary teams.
