AI Architect

Houston, MS - USA

Monthly Salary: Not Disclosed

Posted on: 9 hours ago

Vacancies: 1 Vacancy

Job Summary

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:

Bachelors or Masters 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.

Required Experience:

Staff IC

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 enh...

Job Summary:

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:

Bachelors or Masters 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: