About the Role :

We are looking for a Senior AI Engineer with strong expertise in AI/ML engineering and pricing optimization to build and deploy intelligent solutions for enterprise business operations.

The ideal candidate will combine hands-on experience in machine learning, generative AI, and production-grade AI systems with a strong understanding of pricing strategies, price optimization, demand forecasting, and business decision automation.

Responsibilities :

- Design, develop, and deploy AI/ML models for pricing optimization, price prediction, demand forecasting, price elasticity analysis, and revenue optimization.

- Build intelligent pricing solutions using machine learning, statistical modeling, optimization algorithms, and business rules.

- Develop production-ready AI systems using Python, relevant ML frameworks, and scalable data processing pipelines.

- Apply advanced techniques such as predictive modeling, time-series forecasting, causal analysis, and optimization to solve complex pricing problems.

- Explore and implement GenAI, LLMs, and agentic AI capabilities where relevant to pricing intelligence, recommendations, and automated decision-making.

- Build and integrate AI services, APIs, and data pipelines into enterprise applications and business workflows.

- Collaborate with data engineers, product teams, domain experts, and business stakeholders to translate pricing requirements into scalable AI solutions.

- Evaluate model performance, explainability, accuracy, and business impact; continuously improve models using feedback and production data.

- Establish best practices for model deployment, monitoring, scalability, reliability, and responsible AI.

- Provide technical guidance to engineers and contribute to solution architecture and engineering standards.

Requirements :

- 10 - 15 years of experience in AI/ML engineering, data science, or related technical roles, with substantial hands-on experience building production-grade AI solutions.

- Strong proficiency in Python and ML libraries/frameworks such as scikit-learn, PyTorch, or TensorFlow.

- Strong understanding of statistical modeling, predictive analytics, optimization techniques, and machine learning algorithms.

- Experience in pricing analytics, price optimization, demand forecasting, price elasticity, revenue management, or related commercial analytics.

- Experience working with large datasets, feature engineering, data pipelines, and model evaluation.

- Hands-on experience deploying and maintaining ML models in production environments, including model monitoring and performance optimization.

- Understanding of cloud-based AI/ML services and scalable deployment architectures on AWS, Azure, or GCP.

- Strong SQL skills and experience working with structured business data.

- Excellent problem-solving, communication, and stakeholder collaboration skills.