Job Summary:We are seeking a Houston based technically deep and visionary AI/ML Engineer to lead the development and deployment of agentic AI solutions and drive enterprise-wide data standardization. This in office 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.
