We are looking for a Senior AI Engineer who can translate business problems into scalable analytical solutions and lead the design of AI-driven solutions. You will work at the intersection of data, domain, and decision-making, collaborating with engineering and strategy teams to operationalize machine learning in real-world contexts.Key ResponsibilitiesLead end-to-end AI driven initiatives — from problem framing and data exploration to model deployment.Build and optimize predictive, prescriptive, and generative models using modern ML techniques.Partner with data engineering teams to ensure robust data pipelines and governance for model reliability.Define and implement model evaluation frameworks — accuracy, drift detection, explainability, and impact metrics.Mentor junior data scientists and analysts; establish coding and experimentation best practices.Collaborate with business stakeholders to identify high-value AI use cases and prototype proofs of concept.Required Skills & Experience10+ years of total experience, with 5+ years in applied data science or machine learning.Expertise in Python, SQL, and ML libraries (scikit-learn, XGBoost, PyTorch, TensorFlow).Strong foundation in statistics, optimization, and data storytelling.Experience with cloud environments (AWS, Azure, or GCP) and MLOps frameworks (SageMaker, MLflow, Kubeflow).Exposure to LLMs, NLP, or Generative AI for applied use cases.Ability to translate domain-specific challenges into measurable data science outcomes — ideally in energy, commodities, or financial analytics.Excellent communication and mentoring abilities; comfortable working in client-facing roles.Nice to HaveExperience integrating data science into data platforms or governance frameworks.Prior experience in consulting or product environments.