AI Governance & Model Lifecycle Architect

USA (Hybrid)

Role Location ; Texas, USA Work Model: Hybrid (In-office / Remote) Employment Type: Full-Time Compensation Range: USD 130000 - 180000 Job Overview Experience 7 to 9 Years We are seeking an experienced and innovative AI/ML Architect to design, lead, and deliver scalable artificial intelligence and machine learning solutions aligned with business objectives. This role will be responsible for defining end-to-end AI/ML architectures, selecting the right technologies, and guiding cross-functional teams to build high-impact, AI-driven products. The ideal candidate brings deep technical expertise, strong architectural vision, and the ability to translate complex business requirements into robust AI/ML solutions. Key Responsibilities Design and define end-to-end AI/ML system architectures, including data ingestion, pipelines, model development, deployment, and performance monitoring. Collaborate closely with business stakeholders to understand objectives and convert them into scalable technical AI/ML solutions. Evaluate, recommend, and standardize AI/ML frameworks, tools, and platforms based on business and technical needs. Establish best practices, governance standards, and architectural guidelines for AI/ML model development, testing, deployment, and lifecycle management. Lead, mentor, and provide technical guidance to data scientists, ML engineers, and software developers throughout solution implementation. Ensure AI/ML solutions are scalable, secure, reliable, and maintainable across environments. Oversee seamless integration of AI/ML models with existing enterprise systems, applications, and IT infrastructure. Monitor solution performance and drive continuous improvements in model efficiency, accuracy, and operational stability. Qualifications & Experience Required Qualifications Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, or a related field. Proven experience working as an AI/ML Architect, Machine Learning Engineer, or Senior Data Scientist. Strong hands-on expertise in machine learning algorithms, deep learning, natural language processing (NLP), and computer vision. Technical Skills Proficiency in AI/ML frameworks and libraries such as TensorFlow, PyTorch, Scikit-learn, or equivalent. Experience with cloud-based AI/ML platforms including AWS SageMaker, Google AI Platform, or Azure Machine Learning. Strong understanding of data engineering concepts, big data technologies, and data pipeline architecture. Advanced programming skills in Python, R, or Java. Practical experience with containerization and orchestration tools such as Docker and Kubernetes. Familiarity with CI/CD pipelines and MLOps practices for model deployment and lifecycle management. Soft Skills & Competencies Strong analytical thinking and problem-solving capabilities. Excellent communication skills with the ability to explain complex technical concepts to non-technical stakeholders. Proven leadership and mentoring abilities in cross-functional technical teams. Ability to manage multiple priorities and deliver solutions in a fast-paced environment. High standards of professionalism, accountability, and technical integrity. Benefits & Rewards Full-time employees are eligible for a comprehensive benefits package, including: Paid vacation, sick leave, and company-recognized holidays 401(k) retirement plan with employer matching Medical, dental, and vision insurance coverage Life insurance, disability coverage, and voluntary benefit options Health Savings Account (HSA) and Flexible Spending Accounts (FSA) Benefits may vary based on employment type and location.