Sr IT Data & AI Architect
Sr IT Data & AI Architect
Posted on :
23-09-2025
Employer Active
1 Vacancy
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Monthly Salary
Not Disclosed
Salary Not Disclosed
Vacancy
1 Vacancy
Posted on :
23-09-2025
Job Description
Sr IT Data & AI Architect
Location: Memphis Metro Area - Byhalia MS
Full time role
Key Responsibilities:
Design and implement robust data architectures that enable real-time analytics data integration and seamless information flow across the organization.
Develop a scalable and secure data ecosystem that supports enterprise-wide analytics and AI applications.
Define AI strategies identify opportunities for AI implementation and align AI initiatives with business objectives.
Design enterprise AI architecture including data pipelines machine learning models and integration with existing infrastructure with focus AI/ML solutions tailored to enterprise productivity improvements and battery manufacturing processes including predictive maintenance quality assurance process optimization and yield improvement.
Establish data governance frameworks ensuring data quality consistency integrity privacy and compliance with industry standards (e.g. ISO GDPR industry-specific regulations).
Work closely with CIO AI & Data Leader engineering manufacturing quality and IT teams to understand business requirements and translate these into scalable AI-powered solutions.
Stay abreast of emerging technologies in AI machine learning IoT big data and cloud computing.
Evaluate and implement relevant tools platforms and frameworks for advanced analytics and manufacturing automation.
Integrate data from diverse sources such as manufacturing equipment IoT sensors ERP systems such as SAP and supply chain platforms to enable a connected data-rich environment.
Establish AI Governance framework oversee the end-to-end lifecycle of AI/ML models-data acquisition model development validation deployment monitoring and retraining.
Architect systems to manage and process large-scale data efficiently ensuring high availability reliability and performance for real-time and batch operations.
Provide guidance and mentorship to data scientists engineers and analysts fostering a culture of innovation and continuous learning within the data and AI domain.
Maintain comprehensive documentation of architecture models and processes.
Promote best practices in data engineering AI development and MLOps.
Qualifications:
Bachelors degree in Computer Science Data Science Engineering or a related field; Masters degree preferred
10 years of experience in the Information Technology field with a minimum of 7 years of experience in data architecture data engineering or AI solution development preferably in a manufacturing or industrial environment.
Proficiency with data modeling database management (SQL and NoSQL) and ETL processes.
Extensive experience with AI/ML frameworks (e.g. TensorFlow PyTorch Scikit-learn) and data analytics platforms (e.g. Databricks Spark Hadoop).
Practical knowledge of IoT integration and handling time-series sensor data in industrial settings.
Experience in cloud technologies and services (e.g. AWS Azure GCP) for data storage processing and AI model deployment.
Experience in establishing data governance protocols and ensuring regulatory compliance.
Experience in programming languages such as Python Java or Scala.
Proven ability to design end-to-end AI-driven solutions for process optimization predictive maintenance or quality control.
Excellent communication skills and the ability to engage technical and non-technical stakeholders effectively.
Ability to envision and realize novel applications of data and AI in a manufacturing context.
Strong understanding of manufacturing processes systems integration and digital transformation.
Analytical approach with a track record of resolving complex technical challenges using data-driven methodologies.
Capability to lead cross-functional teams and champion data and AI initiatives across department.
Comfortable navigating ambiguity and thriving in a fast-paced rapidly evolving environment.
Preferred Skills:
Previous experience in the EV automotive or battery manufacturing sectors.
Knowledge of materials science data battery chemistry or electrochemical modeling.
Familiarity with digital twin technologies and simulation platforms.
Certification in cloud architecture data engineering or machine learning.
Experience with MLOps and continuous integration/continuous deployment (CI/CD) pipelines for AI/ML models.
Employment Type
Full-time
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