AI Architect

Job Summary:

We are seeking a technically deep and visionary AI/ML Engineer to lead the development and deployment of agentic AI solutions and drive enterprise-wide data standardization. This role is pivotal to our AI transformation journey, enabling autonomous AI agents that streamline operations, enhance decision-making, and unlock new efficiencies across the organization. The ideal candidate will possess a hybrid skill set spanning machine learning, data engineering, and software development, with a passion for building scalable AI systems and a strong foundation in data governance.

Key Responsibilities:

• Design, develop, and deploy agentic AI systems that autonomously execute multi-step workflows across business functions (e.g., IT, HR, Finance, Operations).
• Collaborate with cross-functional teams to identify high-impact AI use cases and translate them into technical solutions.
• Build and maintain robust ML pipelines, including data ingestion, model training, deployment, and monitoring (MLOps).
• Lead data standardization initiatives to ensure high-quality, consistent, and AI-ready data across systems.
• Partner with data engineering and IT teams to define and implement data governance frameworks, taxonomies, and metadata standards.
• Monitor and optimize AI model performance in production environments, ensuring reliability, scalability, and alignment with business goals.
• Serve as a technical advisor on AI/ML best practices, tools, and emerging technologies.
• Support change management efforts to improve data literacy and promote standardization best practices
• Stay ahead of industry trends and maintain compliance with evolving regulations affecting AI and data.

Required Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field.
• 5 years of experience in machine learning engineering, data science, or AI solution development.
• Proven experience deploying ML models into production environments using cloud platforms (e.g., Azure, AWS, GCP).
• Proficiency in Python and ML frameworks such as TensorFlow, PyTorch, Scikit-learn.
• Strong understanding of data structures, algorithms, and software engineering principles.
• Experience with data governance, data quality frameworks, and enterprise data architecture.
• Familiarity with MLOps tools and practices (e.g., CI/CD for ML, model monitoring, versioning).
• Excellent communication skills and ability to collaborate across technical and non-technical teams.

Preferred Qualifications:

• Experience building or integrating AI agents or autonomous systems.
• Knowledge of enterprise systems (e.g., ERP, CRM) and their data structures.
• Familiarity with data visualization tools (e.g., Power BI / SSRS) and SQL.
• Experience with multi-agent systems or agent orchestration frameworks.