Job Description

Experience Required:

8-10 years in IT, with a minimum of 8 years focused on AI/ML solutions architecture, development, and deployment.

Key Responsibilities:

Architect and design robust, large-scale AI/ML solutions across multiple domains, including Generative AI. Lead and oversee the complete machine learning lifecycle, encompassing data ingestion, feature engineering, model development, deployment, and continuous monitoring. Partner with business and technical stakeholders to translate requirements into scalable and efficient ML systems. Establish and enforce best practices, standards, and governance frameworks for ML pipelines, MLOps, and data platform management. Provide mentorship and technical guidance to data scientists, ML engineers, and solution architects. Assess emerging AI/ML technologies and drive their adoption within enterprise environments. Ensure AI/ML solutions meet security, compliance, and performance benchmarks.

Required Skills & Qualifications:

Deep expertise in Generative AI, Agentic AI, machine learning, deep learning, NLP, and big data ecosystems. Proficiency with ML frameworks such as TensorFlow, PyTorch, and Scikit-learn; cloud AI platforms including AWS, Azure, and GCP; and MLOps tools like Kubeflow, MLflow, Airflow, Docker, and Kubernetes. Strong understanding of data architecture, API design, and scalable microservices. Hands-on programming experience in Python or equivalent languages. Proven experience delivering enterprise-scale AI/ML solutions. * Excellent leadership abilities, with strong stakeholder management and communication skills.