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 Tensor Flow, 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.