Lead AI Engineer / Expert AI Solutions Architect

We are seeking a highly experienced Lead AI Engineer to spearhead the creation, training, and deployment of advanced AI models that directly solve complex business challenges. This role is critical in applying cutting-edge machine learning and data science techniques to deliver scalable, production-ready AI solutions that drive measurable impact and align with organizational strategy.

*Lead end-to-end development of AI models, from data preparation and training to deployment and lifecycle management.

*Architect scalable machine learning pipelines and frameworks tailored to business use cases.

*Optimize model performance through rigorous training, validation, and tuning strategies.

*Implement best practices in AI development across environments, frameworks, and collaborative workflows.

*Champion the use of automated testing, validation, and monitoring tools for production-grade AI.

*Guide and mentor teams on prompt engineering techniques and model refinement for generative and predictive AI use cases.

*Ensure robust version control for AI models, integrating tools like Git with ML workflows.

*Collaborate cross-functionally with data engineering, product, and DevOps teams to ensure alignment and scalability.

*Maintain security, compliance, and performance across AI infrastructure and data systems.

*AI Development Best Practices

*AI Model Lifecycle Management

*AI Model Training Optimization

*Prompt Engineering

*Version Control for AI Models (e.g., Git)

*Automated Testing & Validation Tools for AI

*Collaborative AI Development Platforms

*Deep understanding of AI Development Environments & Frameworks

*Data Preparation and Feature Engineering

*Model Development & Hyperparameter Optimization

*Performance Analysis and Root-Cause Debugging

*AI Frameworks: TensorFlow, PyTorch

*Development Environments: Jupyter Notebooks, Google Colab

*Version Control: Git, DVC

*Compute Infrastructure: GPUs, TPUs

*AI Platforms: AWS SageMaker, Azure ML

*Infrastructure Management: Docker, Kubernetes for ML

*Data Security: Role-based access, encryption standards in AI systems

*6+ years in machine learning, AI engineering, or applied data science roles.

*Proven experience deploying models in production at scale.

*Strong knowledge of MLOps and AI/ML governance practices.

*Advanced degree (MS/PhD) in Computer Science, Artificial Intelligence, or a related field is a plus.